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Artificial intelligence in the creative industry: replacement of people or assistant

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The possibilities of neural networks are now being actively discussed in the media space, and artists fear them as competitors for commercial orders. Let’s figure out which business tasks AI is suitable for, and where humans are still indispensable

Artificial intelligence in design: pros, cons, pitfalls

Let’s start with the positives.

Speed. Artificial intelligence (AI) algorithms can complete tasks much faster than any designer, thereby saving significant time and increasing efficiency.

Price. AI algorithms can automate many tasks, reducing the need for manual labor and reducing costs. For example, the automated preparation of technical specifications for designers or the generation of several design options from which a specialist can build.
Accuracy.

AI algorithms are capable of performing precise, detail-oriented work, which makes them ideal for solving certain design problems, such as generative graphics creation, brand identity design, website and user interface design, logo design, and so on.

It all depends on the request and the task, but it is important to consider that without understanding the processes, everything is narrowed down to the generation of objects and elements for the sake of those very objects and elements. Therefore, you need to build the right queries and be able to adapt and integrate the resulting solution into the product.

Now to the cons.

Dependence on human participation. AI is currently not capable of inventing anything entirely on its own. Accordingly, like any machine, a neural network must be trained—the system requires direct human participation, including design goals and training data. They are not capable of inventing themselves.

Lack of creativity. AI is not capable of true creativity – their designs are strictly limited to the given parameters on which they learn.

Inflexibility. AI algorithms are limited by their programming and may not be able to adapt to changes or new requirements.

It’s also worth noting that while AI has the potential to revolutionize the design and creative industries, it’s important to understand its limitations and limitations. Although it can perform certain tasks faster and more economically than designers, AI is not capable of true creativity and is directly dependent on human input.

Ultimately, AI is just a tool to help designers, but it is not a replacement for human creativity and intuition. The neural network creates a form that still has an idea behind it.

Where to apply artificial intelligence now

Following the conclusions from the previous part, AI is an effective tool to simplify the designer’s work and reduce time costs. Here are a few tasks where a neural network can help today:

Content Creation

AI can generate design artifacts: images, logos, illustrations, freeing up resources for designers to focus on user experience tasks and spend less time searching for a graphic element.

UX Design

AI can be used to analyze user behavior and make design changes to improve the user experience. Take Invision, for example , which has integrated artificial intelligence technology into its service to enable automated design specifications, image recognition and design proposals based on industry best practices.

Interface design

AI can generate designs based on user preferences, allowing designers to focus on creating the most attractive and convenient experience for users. This is how Uizard integrated AI into their platform to automatically create responsive designs.

Interactive Design

AI can be used to create interactive designs that respond to user behavior in real time, making them more engaging and intuitive. Google has integrated AI into the Flutter platform  , a fun, gamified way for millions of people to train Google’s artificial intelligence and machine learning models, helping products like Google Translate, Maps, and Photos better serve users across different regions and cultures.

Typography

AI can be used to generate font styles and layouts, reducing the time designers spend on it.

Font from the Austrian studio Process, created by a neural network (Photo: Process)
AI Type used AI in its platform to automatically generate fonts based on user preferences.

These are just a few examples of how AI is being integrated into the work of designers and companies. Using neural networks, tools are created to optimize work and reduce time costs, while maintaining creative control.

Additionally, it is worth mentioning Midjourney, ruDALL-E and similar services that convert text into a graphic element. A service built on a neural network allows you to create an image quickly, beautifully and effectively, but it cannot independently form the context – the latter always remains on the side of the person. And with the correct work of a specialist, the tool allows you to create excellent graphic elements that can be adapted for a specific task.

What will a neural network not be able to take on in the near future? And what does this mean for professionals and companies?

While artificial intelligence has the potential to revolutionize many aspects of the design and creative industries, there are certain tasks that it is not yet capable of and is unlikely to be capable of in the near future. These tasks require a level of creativity, intuition and empathy that is beyond the capabilities of algorithms.

Conceptualization

AI algorithms cannot generate new ideas or concepts, they can only work with what they have been trained to do. Designers and creative professionals will continue to play a major role in developing project concepts.

Emotional connection

AI algorithms are unable to create an emotional connection with an audience through design. Designers bring their own experiences, perspectives and emotions, allowing them to create designs that resonate with their target audience.

Cultural sensitivity

Artificial intelligence is unable to understand cultural codes and its inherent nuances, which means it can create designs that are insensitive or offensive. Designers with a deep understanding of cultural differences will continue to play an important role in ensuring that design is culturally appropriate.

Human-centered design

AI algorithms are unable to take a human-centered approach to design because they are unable to understand the needs, wants, and experiences of users.

These limitations mean that designers and creative professionals will continue to play a critical role in the creative industry—there will always be a place for human intuition in these areas. Companies and organizations must invest both in AI technologies and in the development of their own employees in order to be able to use the benefits of AI to the maximum, thus building a “partnership” interaction between man and machine, where AI can be an excellent tool for saving time and resources for implementation .

Don’t go to a fortune teller: what is the profession of a futurologist?

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The answers were prepared by Kirill Ignatiev, coordinator of the project “Technical Progress and the Economy of the Future”, Chairman of the Board of Directors of the Russian Investments group of companies, lecturer at RANEPA, member of the ASI expert council

1.Who is a futurist?

A futurologist analyzes trends of the present and predicts the future. Often different people are called futurologists: popularizers of science, trend watchers (business consultants), and visionaries. Some believe that they are different, others believe that the concepts are synonymous.

Visionaries have a creative rather than a scientific view of the future. These are strategists who sense trends, determine development vectors, isolate the main thing from the flow of information and convey it to the masses.

Visionaries are often called Elon Musk, Jack Ma or Bill Gates. There are also science fiction writers, who once, one might say, began the increased interest in predicting the future. But this is still a separate creative area.

Futurology as a science was formed relatively recently, largely from philosophy and sociology. It now sets itself more precise goals than before and is based on technological, technical and engineering areas. This is a technique that has been developed over the years and focuses on studying the dynamics of key trends.

2.How to become a futurist?

Futurologists are now almost never taught anywhere, although some universities still introduce separate master’s and doctoral programs in predicting the future, as well as courses in analytics and strategic thinking as part of additional education.

So, you can study to become a futurologist, for example, at the Free University of Berlin, the University of Hawaii at Manoa or the University of Houston. However, you can become a futurologist by obtaining a more familiar specialty – business administration, marketing, sociology, philosophy, anthropology are suitable. The combination of these disciplines with systems analysis and engineering competencies is even closer to futurology.

3.What skills does a futurist need?

There are no established professional standards, but practicing futurologists agree that it is necessary to read a lot, understand technological, technical and social world processes, track scientific discoveries, identify trends in business and politics, know languages, and also develop analytical and strategic thinking and be able to sometimes extrapolate existing statistical trends into the future.

4.What trends do futurologists study?

The movement of technology from science to R&D (research and development) and business. In essence, this is the process of introducing into everyday practice inventions that have already been experimentally confirmed or close to it.

Studying technologies already used in business, which tend to become cheaper. Such technologies are most promising for distribution in the future. An example is smartphones. They’ve come down so much in price that today’s top phones are the same price as Motorola’s top models from the 1990s. But at the same time, modern smartphones are completely different devices.

The technology has become very complicated, devices have become thousands of times more accurate, but the price has remained the same.

Study of the younger generation. This is a kind of test: if today the technology is mastered by children, then, most likely, tomorrow adults will master a similar solution. Plus, children will be the main players in the future, those who will live in it. Therefore, we need to carefully study everything that the younger generation lives with in order to draw conclusions about the upcoming changes.

Studying trends in the field of communications and any creativity. These areas anticipate the future. Today, new horizons have been opened by social networks; tomorrow,

technologies for accessing the vision of another person or online presence will do so. You can also find a lot of ideas about the future in art, science fiction literature and films.

Studying everything that happens in the leading industries that can be called big-budget and that are shaping the future. For example, the automotive industry has long determined the development of industrial design, since a lot of money has been invested there. Space and the military industry shaped the future of information distribution and security, as well as the most sophisticated computer solutions and materials.

5.Is there a limit to predictions?

A forecast covering a period of no more than 9–10 years can be practically useful for business. The rest is closer to science. Forecasts beyond ten years are useful for science, as it storms distant horizons and potential opportunities that will be applied in practice.

Science must plunge about a century into the future, otherwise unexpected inventions will not appear, new continents will not be discovered in the broad sense of the word.

6.Where should a futurologist go to work?

The idea of ​​having a futurist on staff will soon be reconsidered. As a futurist, I believe that the very concept of company staff will soon become a thing of the past. Large corporations will increasingly rely on the free labor market and will attract more and more freelancers and self-employed people. Futurologists will primarily be among these workers. They will become consultants, hired for a certain period of time to develop recommendations.

People with a scientific and systematic approach will be in demand in the future in various professions. A vision of the future is needed for engineers, chemists, doctors, and designers. The model of today is as follows: to create a product of the future that will be interesting to the market, it is necessary to attract specialists from a variety of professions who have the competencies of a futurologist.

A futurologist can also engage in other activities and, as a scientist, philosopher or teacher, integrate his vision of the future into his work.

Building the future: how the digitalization initiative will change the construction industry

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Digital transformation has become a new national goal for Russia’s development. It will affect all sectors of the economy. We talk about plans for digitalization of construction and projects that are already working in this direction

Digital maturity

An indicator of how actively advanced IT technologies are used in a particular industry is their digital maturity. According to the development strategy adopted by the Russian Ministry of Construction, the construction and housing and communal services sector should reach this maturity by 2030. For this purpose, it is already undergoing large-scale transformations, namely:

Bringing all mandatory activities in the field to a single standard in electronic form: construction itself, as well as reconstruction, engineering work, architectural design, cadastral registration, receipt and transfer of land ownership rights, etc.

Introduction of information modeling technology (BiM – Building Information Modeling).

This is an approach in which a general information model is created for a construction project, which includes all architectural, technological, economic and other decisions related to it.

Launch of the super service “Digital Construction of Individual Residential Buildings”  – a kind of “Government Services” in the construction industry – a single platform for providing relevant services to citizens and legal entities.

Creating conditions for interaction between examination bodies and construction market participants in a unified digital environment. One example is the examination of project documentation within the “one window”.

Development of a new project management system for government customers.

First results

Various measures for digitalization of the construction industry are now being implemented in 15 pilot regions, including the Moscow region, St. Petersburg, Tyumen region, the republics of Tatarstan and Bashkortostan, Krasnodar Territory and others. Another 25 regions will join them in the near future. The first sign in this process, of course, was Moscow. For example, in the capital there is already a construction management information system with electronic document management, which creates a single space for interaction between all participants in the industry market.

According to forecasts, the digitalization project should have a positive impact on the completion time and cost of construction services, namely: optimize procurement costs by up to 15% and reduce deadlines by 20%. The first results are already visible: the time for delivery of objects is reduced by about 10%, and the approval and signing of documents for individual objects occurs five to six times faster, the Russian government notes .

It is important to note that the basis for the entire digitalization initiative is precisely domestic projects and developments. They occupied this niche after many Western companies left the Russian market. Most large developers now have their own IT departments that are working on the digitalization of their processes.

Some of them, having created successful products and tested them within the company, began to offer them on the open market. Now IT solutions, entirely created in Russia, are making a major contribution to the development and creation of a high-tech future in the construction industry.

“Russian analogues have been on the market for quite a long time and have proven themselves to be full-fledged, original and competitive products. We are talking about a whole ecosystem of Russian-made products,” says Deputy Prime Minister Marat Khusnullin.

Support for leadership projects

For the successful digital transformation of the economy, not only the IT tools themselves are important, but also a competent management strategy and clearly structured business processes. Without this, even the most popular product may not achieve significant growth and development.

Therefore, to help promising startups, the Agency for Strategic Initiatives (ASI) has existed in Russia since 2011. This is an autonomous non-profit organization, one of the main goals of which is to support socially significant projects in the field of technology, education, social sphere, creative industry, and ecology.

ASI supports startups free of charge. Assistance includes promotion of projects (including to international markets), search for partners, consultations on working with federal and regional authorities, expertise in various fields, acceleration, information support and at specialized events.

Svetlana Egelskaya, director of the ASI leadership project management center:

“To support projects, our Agency has created a portfolio of tools and services that have shown their effectiveness and have already helped many companies take off – to become market leaders, remove regulatory barriers, replicate, and attract financing.”

Over the entire period of its work, ASI received more than 10 thousand project applications. Currently, the organization’s specialists review about 2 thousand project applications per year. The digital transformation of construction and related projects also, of course, fall into the sphere of interests of ASI. And here are some of the most interesting of them.

“ORLAN System”

An ecosystem that allows you to unite all participants in the construction industry in a single digital space, making interaction between them more transparent and efficient. The core of the platform is a specialized marketplace, around which additional government, financial and marketing tools and services are developed. Participants can sell their own goods and services, control procurement processes, create and sign smart contracts and other documents electronically.

Andrey Lupy, director and owner of ORLAN System:

“We have digitized the process of purchasing and supplying building materials to sites, created a unique database of real manufacturers of building materials, and are promoting a solution for purchasing materials without intermediaries. “ORLAN System” has become ASI’s leading project, which has allowed us to build a high-quality dialogue with government agencies and large companies to promote our platform.”

SODIS Building CM

A platform for automating construction processes – from design to commissioning. Allows you to monitor the progress of construction and manage processes in a single information space. Improves the quality of management, speeds up delivery deadlines and saves budget.

PropTech.OnLine

Cloud-based modular ecosystem for construction management. Allows you to automate the relationships of all participants in the development process: customer, investor, general contractor and general designer, contractors, suppliers, buyers and others.

Yulia Lesnaya, Marketing Director of PropTech Group:

“ASI not only connects us with interested customers, but also invites us to speeches and events where we can present our solutions to a wide audience. Thanks to this, we are able to attract new clients and expand our activities. Now we continue to cooperate with the Agency and have already submitted an application to support a new project on smart concrete monitoring . ”

RTIM

A software package based on artificial intelligence for creating master plans for territory development. Allows you to quickly and accurately model urban planning and socio-economic scenarios for the development of territories, based on the analysis of big data.

BIMIT

A program for creating digital twins of buildings based on BIM information modeling technology. The BIM model of an object includes all the data and decisions on it, which helps to significantly increase the accuracy of design work, check the model for compliance with requirements and standards, eliminate errors before construction begins, and track costs at each stage. As a result, the project implementation time and the costs of its operation are reduced.

Vera Berezina, director of BIMIT:

“The implementation of capital construction projects is a complex process, several dozen people are involved in it step by step, so problems always arise with timing, transfer and updating of information, and cost overruns over planned estimates. With digitalization, many processes speed up, become transparent, and the efficiency of communication between participants increases. Our BIMIT software project passed the competitive selection for the ASI program and received the first and most necessary support for product development in the early stages.”

IYNO

A set of tools for construction management based on information modeling of buildings and structures. Allows you to collect and process data in real time, conduct analytics and find optimal scenarios for implementing business processes. Using the IYNO platform, you can mark various violations and defects, monitor the work of contractors and the timing of its completion.

 

Pervasive artificial intelligence: what happened in IT in early autumn

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Most startups are developing neural networks for various industries, fintech is developing AI solutions, and payment services are appearing on social networks. About events in the IT world – in the material “Xu Techs”

Glossary

Explainable Artificial Intelligence (XAI) is a branch of artificial intelligence that aims to make the decisions and actions of AI systems and AI models more understandable to people.

The digital currency of central banks (Central Bank Digital Currency, CBDC, or CBCB) is a digital analogue of national fiat currencies (traditional currencies, such as rubles, dollars, yuan), which are issued, regulated and guaranteed by central banks (CB).

Generative AI (GenAI) is a category of artificial intelligence (AI) algorithms that can generate new results based on the data on which they are trained.

A Large Language Model (LLM) is a deeply trained neural network used for natural language processing.

HNWI (High Net Worth Individuals) are high-income individuals whose capital ranges from $1 million to $30 million.

UHNWI (Ultra High Net Worth Individuals) – individuals with a net worth of at least $30 million.

The digest was prepared by the red_mad_robot analytical center.

Trends of the month: explainable AI, AI hype, and cross-platform from Apple

Explainable AI integrates into people’s lives and work

Explainable AI systems and models are increasingly being used in areas such as healthcare, banking, education, agribusiness, and industry, where the consequences of errors or biases can be serious or even fatal for a business. Therefore, XAI has become a more important area. Here are the latest industry trends.

Concept-based explanations. A way to “explain” AI decisions in high-level concepts such as emotions, goals, values, or categories. For example, a conceptual explanation of facial recognition systems might say that the AI ​​model identifies a person as happy because they have a smile on their face, raised eyebrows, and open eyes.

Counterfactual explanations. These are, as a rule, hypothetical reasoning, thought experiments. The actual result is compared with the alternative, and the factors that led to a particular decision are highlighted. For example, if we explain the possible refusal of an AI model to approve a loan, then the reasons may include the applicant’s insufficiently high income, large debt, or insufficiently good credit history. Moreover, it will indicate how much each factor influenced the AI ​​model’s decision making.

Interaction with the model. Users can interact with the AI ​​model to receive explanations for its behavior. For example, a person can find out why the AI ​​chose a particular treatment or medicine. This increases the user’s level of trust and also gives the user the opportunity to gain new knowledge by understanding the logic and assumptions behind the algorithms.

The startup market is experiencing AI hype

In September 2023, Y Combinator (YC) held a Demo Day. AI has completely taken over the startup market: more than 60% of startups presented at this accelerator season are related to artificial intelligence technologies. Startups are increasingly developing AI solutions for specific verticals and sectors. These sectors can be anything, the main thing is the huge market potential and its volume. For example, AI for banking, education, retail, etc.

Success, according to YC, is finding pain and problems in corporations or corporate business processes and solving them using a niche AI ​​service or AI model.

Apple will promote cross-platform

Apple does not mention artificial intelligence in its announcements, unlike Microsoft and Google, which put forward ambitious concepts for the development of AI. But that doesn’t mean Apple isn’t developing it. First, the company is developing an AI-based chatbot to compete with ChatGPT. Secondly, several AI features were presented at the Apple Wonderlust conference. For example, with the help of neural networks, the iPhone 15 has improved noise reduction, background blur for portrait photography, and predictive text. And in the latest Apple Watch Series 9 Neural Engine, thanks to machine learning, Siri accuracy will increase by 25%.

At the same time, the company has another direction – cross-platform in the overall ecosystem of products (the ability to work with several hardware platforms at once). In early September, Apple announced the App Store for the Vision Pro mixed reality headset. The project is almost ready for use: bigtech notes that the beta version of VisionOS from the App Store will be released before the end of autumn this year.

New AI kit: “money on autopilot”

One of the most important advances in generative AI is the ability to process and create not only text, but images and other forms of content. The use of this technology in the field of consumer financial services was analyzed by the a16z venture capital fund, predicting the emergence of “autopilots” that could bring to life the idea of ​​“self-propelled money.” In the future, the cost of applying for services will be virtually reduced to zero, which will allow the “autopilot” to constantly search the data set for the best conditions “without hands.”

This innovation, on the one hand, can democratize financial planning, on the other hand, create problems for financial institutions, such as a decrease in customer loyalty and an increase in the number of applications. Financial institutions will need new AI-powered tools to accurately assess transaction intent, combat fraud, and process applications more efficiently.

Events of the month

AI is taking fintech by storm. British fintech company Trade Ledger is implementing an AI bot based on Azure OpenAI (a cloud platform from Microsoft). The bot personalizes reports and offers clients suitable loan terms. Fintech company HighRadius has launched the FreedaGPT neural network, which combines the company’s developments and the OpenAI model: it answers questions in letters and can generate reports on financial requests. Software company Temenos has developed GenAI to automatically classify customers’ banking transactions.

Going beyond the social network . X (aka Twitter) is making moves in the payments space: the social network recently received a money transfer license in several states. WhatsApp in India now offers the ability to pay for goods and services.

Focus on ESG . Swedish fintech company Klarna has launched features that help users make “informed” purchases. The service allows you to compare prices from thousands of retailers and filter product search results by characteristics (color, size, customer ratings); The latest update adds a special filter to highlight conscious brands that have received a sustainability rating of 4 (good) or 5 (excellent) from Klarna partner Good On You.

Neuronews . According to business intelligence platform Crunchbase , in the first half of 2023, one in four dollars invested in US startups went to AI-related companies. Analysts from Innopolis University are confident: the volume of the AI ​​market in Russia has grown from 240 billion rubles. in 2019 to more than 600 billion rubles. in 2022. Leading positions in the development and implementation of AI are occupied by Yandex, VK and Sber. Here are some recent news from the global and domestic industry.

Yandex plans to adapt the YandexGPT neural network for the Middle East markets. The company has also resumed testing self-driving cars in the US, but under the Avride brand.
By the way, about the Middle East. The Abu Dhabi Institute for Technological Innovation has publicly released a large language model (LLM) of the Falcon 180B, which takes into account 180 billion parameters. It is superior in quality to open models and GPT-3.5. UAE-based technology company G42 is launching an AI model in Arabic. By the way, Microsoft is ready to cooperate with G42.

Microsoft is teaming up with digital pathology AI solutions company Paige to develop the largest artificial intelligence model for cancer detection.

To create a convenient system for contactless payment and personal identification, Amazon One trained a neural network based on millions of artificial palms.

Google has announced a slew of AI updates. For example, 20 new ready-made AI models optimized for enterprises have been added to the cloud service.

The kick sharing service Whoosh and the Neiry company are testing a scooter that is controlled using a neural interface.

Chinese scientists have demonstrated the SpiralE neural interface, which is presented in the form of a device made of a flexible polymer that transmits signals from the user to the computer. SpiralE is worn over the ear.

China Mobile has launched a 5G supernetwork with support for metaverses. The company also proposes to transfer the social credit system to them.

Hiber3D has introduced the ability to generate worlds for metaverses based on prompts.

Topic of the month: what will happen to fintech

According to a flagship report from consulting firm Boston Consulting Group, the fintech market will grow fivefold to reach $1.5 trillion by 2030, with the Asia-Pacific and North American regions becoming centers of gravity for startups and companies. These markets will be valued at $600 billion and $520 billion, respectively (more than 70% of the total market).

Digital payments (retail, crypto payments, b2b) and digital lending will dominate the market and generate about 60% of all revenue. At the same time, neobanking (digital banking), insurtech (insurance technologies), solutions for the development of financial infrastructure and wealthtech (technologies for wealth management) will also grow.

In general, investments are evenly distributed across regions, but there are differences in priority segments. For example, in developing regions, investors see prospects in payments and lending, and in developed regions – in financial infrastructure and wealthtech.

Several interesting trends by segment:

Digital payments . Instant payments will become the mainstay for many countries. CBDCs are gaining momentum, and cross-border payments are ripe for disruption—disruptive innovation.

Digital lending . GenAI, blockchain and ecosystems will become mainstream.
Wealthtech . So far, there is insufficient penetration of HNWI/UHNWI into digital. There will be a strong increase in interest in alternative assets (this is investing in any asset class, with the exception of stocks, bonds and cash) in all countries of the world.

Insurtech . The market will increasingly experience hyper-personalization of offerings due to the growth of consumer lifestyle and health data through wearable devices.
Neobanking . Neobanks for SMEs are becoming increasingly important to investors. The B2b model demonstrates the potential to create a scalable customer base that will allow you to generate stable profits.

How to launch an innovation development program in a company

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In an era where digital is becoming commonplace, innovation creates new competitive advantages for businesses. How to competently build an innovation development program and evaluate the effect of its implementation?

About the expert: Alexander Bogutsky, chief manager of the “Cultivation of Innovation” program at IT_One.

Could it be too late tomorrow? Innovation as the driving force of business

In the 1980-90s, the VUCA concept arose in scientific circles close to the American military structures, the defining idea of ​​which was the instability, uncertainty, complexity and ambiguity of the model of the surrounding reality. In the late 2000s, this concept, which largely challenged traditional ideas about the world order, began to actively take root in the corporate environment. Managers in business practices have adopted the idea of ​​a world whose key attributes are variability ( Volatility ), uncertainty ( Uncertainty ), complexity ( Complexity ) and ambiguity ( Ambiguity ).

This concept was widely used until 2020, until events related to the pandemic and its consequences made adjustments to it. Then VUCA was replaced by the acronym BANI, which more accurately characterizes the “new normal”: fragile ( B rittle), alarming ( A nxious), non-linear ( N on-linear), incomprehensible ( Incomprehensible ).

According to the BANI concept, we do not and cannot have a model that gives a complete understanding of what is happening, and, accordingly, methods that guarantee the accuracy of forecasts and decisions.

The modern world is prone to absolutely unexpected and abrupt changes, to abrupt and unpredictable transformation. But we have the opportunity to understand which management approaches and thinking models are effective in the new reality, and which will limit us.

The key skill for effectiveness in new conditions is not the ability to plan and make forecasts, but the ability to quickly recognize changes and find solutions adapted to them.

In such a paradigm, innovative thinking and innovation become success factors, and sometimes the only condition for survival. We need the ability to operate with a flexible picture of the world, adaptively change mental models and find solutions to problems that seemed impossible just yesterday.

If you do not develop innovations today, tomorrow may be too late. According to the Accenture Technology Vision 2021 report , based on a survey of more than 6 thousand business and IT leaders, companies that use effective digital platforms and quickly adapt to innovation grow revenue five times faster.

At the same time, due to the development of visual programming platforms and special systems based on artificial intelligence, the ability to create and develop digital solutions becomes available to employees performing business functions, that is, not to IT specialists. Information technology is no longer the domain of narrow professionals. What trump cards then remain for specialized IT companies?

Thanks to innovation, the company achieves a number of goals

Ensuring sustainable business growth in new conditions.
Finding a market niche and new competitive advantages in the post-digital era.

Responding to changing customer needs: forecasting and modeling demand, a flexible approach to the development of goods and services.

Qualitative improvement of personnel, creation of a positive image. The most qualified personnel, carriers of an innovative culture, are more willing to work for a company that has experience in innovation.

Simply put, innovation brings profit. This is not only and not so much about the development of new projects, spin-offs, and startups. The focus is on the task of being able to effectively grow a business in a changing reality, timely find successful answers to unexpectedly emerging new challenges, constantly generate and competently implement new ideas.

Innovation matrix: defining goals and choosing a strategy

According to one of the definitions accepted in international practice, innovation is the final result of innovative activity, embodied in the form of a new or improved product introduced on the market, a new or improved technological process used in practical activities or in a new approach to social services. Simply put, innovation is an innovation that has been introduced and ensured a qualitative increase in the consumer qualities of a product or the efficiency of its creation processes .

There is no universal algorithm or universal tools that will ensure the effectiveness of corporate innovation. Each organization has its own specifics, tasks and capabilities. Accordingly, in order to select the most suitable model, it is necessary to decide what goals the company intends to achieve and what resources it can devote to this.

To determine strategic goals in the field of innovation, well-known strategic management tools are applicable. And to identify possible options for the development of innovation and determine a suitable model, you can use a tool such as the “Innovation Matrix”.

The most famous matrix is ​​proposed by the Board of Innovation. The innovation matrix is ​​a square divided into four sections. It has two axes: the vertical one indicates high or low levels of investment in innovation, and the horizontal one indicates a focus on external or internal innovation. Thus, depending on the volume of planned investment (large or small volume) and focus (internal or external projects), it divides innovation strategies into four types: “hunters”, “builders”, “explorers” and “experimenters”.

The Hunter  is an innovator archetype, characterized by a high level of investment in innovation with a focus on external sources. Typically, this type of strategy involves a heavy focus on collaborations with startups, acquisitions, and the creation and financing of new businesses.

Builder  – This type of strategy involves significant investment in innovation, but the development of innovations occurs primarily within the company. This means that Builders are investing significant resources in transforming their organization, creating innovative divisions and spin-offs.

The Explorer , like the Hunter, looks for new opportunities primarily outside of their company. Typically, these are organizations that understand the need to explore new opportunities for their business, but are not yet ready to invest too much. They also see that they lack the internal capacity to innovate, so they mostly look outside the company for new ideas and opportunities.

And finally, the Experimenter . This archetype is typical for those who are just starting their innovation journey and want to move carefully. Experimenters have a lower level of investment in innovation and focus on creating their own innovations. With this strategy, organizations focus their attention on internal work, such as innovative training sessions and testing innovative ideas.

Based on what you want to achieve, you can determine your type of innovation development model, develop an appropriate program and estimate the resources that will be required to implement it. And in implementing this program, you will need to use innovative practices and tools.

An example of an innovative practice with a good set of tools is the TRIZ methodology (the theory of solving inventive problems). TRIZ was developed by the Soviet scientist and engineer-inventor Heinrich Altshuller based on an analysis of 40 thousand patents and a generalization of invention techniques. Although the founder of the theory initially developed it to solve technical problems, later this theory was used to solve any problems of increased complexity. It is suitable for solving creative problems in almost any field. In fact, now mastery of this methodology can be considered as a valuable problem solving skill in the business environment.

Ideas and solutions prepared using TRIZ are an order of magnitude more effective than those implemented without it. This means that applying this practice saves time and resources.

Other successful tools that have proven useful are Design Thinking and Foresight.

Design thinking is classified as a user-centric method, that is, focused primarily on consumers. Key questions that an innovator asks himself: “Who will use my development?” and “How will my development affect the human condition?” In accordance with this, work on innovation here begins with the empathy stage, after which the analysis and definition of the problem, generation of ideas, prototyping and selection of the best solution takes place.

As for foresight , this is a methodology for forming an image of the future, which is based on the assumption that the future is not deterministic. It appeared back in the 1950s-1960s in the USA, but since then has undergone significant changes. Thus, by the 2020s, an “open foresight model” appeared, a variant of which is Rapid Foresight. Researchers work in a collective session, where each participant forms an idea of ​​the future and makes individual decisions within a certain segment of their competencies.

By combining these segments like pieces of a puzzle, analysts get the desired forecast model. It is extremely important that rapid foresight allows, when creating an image of the future, to make maximum use of those sources that, on the way to this future, will occupy influential positions and, to one degree or another, will influence its formation.

Innovation program structure

The main objective of the innovation program is transformation, which leads to the achievement of certain goals. For this process to be effective, a number of mechanisms are used, combining and prioritizing them taking into account the individual characteristics of the company.

1. Innovations are made by people  – and not by individual enthusiasts, but by a team of like-minded people. To engage in innovation on an “industrial scale”, you need to have knowledge of certain practices. If there are many such people in a company, then the company is lucky. But now this is rather an exception to the rule. Most often, it is required to develop innovative thinking skills and knowledge of practices for solving innovative problems in employees.

For this purpose, special training programs are organized with the involvement of relevant experts. These programs are often built on the basis of internationally recognized training standards in TRIZ and Design Thinking. TRIZ training programs, organized according to the standards of the International TRIZ Association, include methods for activating creative thinking. And TRIZ itself is a good tool for solving creative problems. This tool can be mastered by anyone, regardless of their mentality and previous experience.

The second important aspect of the development of innovative thinking is the practice of solving innovative problems. And therefore, these training programs should be combined with solving creative problems that are valuable for the practical activities of the company.

2. It is advisable to form a community of employees interested in the development of innovation and ready to take part in it: a community of innovators. There are many people in the company who are interested in uniting for certain professional goals and interests. One of the goals of such an association is the exchange of information and best practices. In this case, employees can be united around best practices for solving creative problems and solving problems of increased complexity, sharing experience and expertise in solving such problems, and becoming familiar with advanced methods from world practice.

Another unifying factor can be the joint solution of innovative problems that are important for the company. This is attractive both from the point of view of receiving subsequent benefits – encouragement, opening up new opportunities, and satisfaction from a beautifully solved complex and important task.

3. It is required to organize a special system for collecting ideas  – a corporate resource on which everyone can formulate their idea and track its further fate. Separately, it is worth highlighting the system for collecting information on existing innovations. Perhaps the potential of some of them has not been fully exploited.

4. It is not always possible for an employee to independently express an idea in such a way that its value is clear. We need a mechanism that will help formulate and correctly formalize the idea – for example, open meetings of expert councils on innovation. They may have different names, but the essence is the same: this is a place where anyone can come and receive qualified help.

5. A mechanism is required to motivate employees to innovate . It is determined individually for each company, and most often includes both types of motivation – material and intangible. The system of material incentives for an employee is linked to the size of the economic effect that was achieved through the use of innovation. Separate motivation for managers is usually implemented in the form of KPIs. Non-material motivation is an expression of public recognition of an employee’s contribution to the development of innovation: mention in the corporate press, on physical or electronic information resources.

6. Let us note the introduction of the principles of gamification as a relatively new independent motivational mechanism. A competitive incentive appears, for example, as part of an idea competition , where anyone can propose a solution to a problem that has practical value for the company. This is a kind of analogue of hackathons, only the tasks in it are more complex and usually cannot be solved by traditional methods.

Performance metrics

Performance metrics help measure results and determine the extent to which the company’s goals and objectives have been achieved:

Economic goals are varied, but in general they boil down to improving economic indicators (or, as a special case, to ensuring their stability in deteriorating conditions). Traditional metrics for measuring economic impact are used here. A key place among them is occupied by ROI (Return On Investment) – an indicator characterizing the return on investment. In the case of innovation, there is a special name for this term – ROII, Return On Innovation Investment).

Diversification and expansion of business. Metrics: opening new successful business lines, entering new markets, emergence of a spin-off (spin-off of an innovative subsidiary).
Solving important business problems: technological, production organizational, marketing and others. Metric: number of solved problems.

Increasing the attractiveness of working in the company. Metrics: reduction in staff churn rate; an increase in the number of resumes received by the company; reducing the average cost of selecting a candidate for a vacancy due to a higher quality candidate base and reducing the number of refusals of an offer; increasing the attractiveness rating of working for the company in independent surveys (HeadHunter, RBC and others).

Increasing the degree of creativity of the company’s team and preparedness to solve problems of increased complexity.

Correctly assessing trends and anticipating the future is difficult. In world practice, there are many examples of both successful and unsuccessful innovations. But the most striking cases still show how a missed chance to develop an innovation led to serious consequences for the business. The story of Kodak, which failed to adapt properly to the rapidly advancing era of digital photography, is a classic illustration of this.

That’s why it’s worth thinking seriously about innovation now: considering strategies, studying tools, involving people and building a community.

Sustainable algorithms: how artificial intelligence drives the ESG agenda

Neural networks help build a sustainable future: curb global warming, preserve nature, develop smart cities and solve social problems. We talk about the most interesting AI solutions for ESG transformation

There are technologies that have changed the path of human development, immeasurably increased human potential and created the world to which we are accustomed today: fire, the wheel, printing, telegraph, computer. In the 21st century, such an iconic technology is artificial intelligence (AI). It not only raises a person’s capabilities to a new level, but also helps to harmonize relationships with the outside world.

Neural networks have become one of the most important tools for achieving sustainable development goals, and today artificial intelligence technologies are making a significant contribution to the well-being of society, business and the planet.

Carbon neutrality and forest conservation: AI to combat climate change
Temperatures on Earth have already risen 1.1ºC above pre-industrial levels, the Intergovernmental Panel on Climate Change (IPCC) says . As a result, extreme natural events are increasingly occurring, causing enormous damage – on average, its economic assessment over the past 20 years has reached $16 million per hour .

Global warming is undermining humanity’s efforts to achieve the UN Sustainable Development Goals (SDGs), experts from the World Meteorological Organization warned in September. It is obvious that the problem requires new approaches and solutions. Nature stated that AI will be able to help achieve 79% of the SDGs thanks to its powerful analytical capabilities. AI provides greater insight into vast amounts of data to develop powerful, simple tools to improve climate resilience and natural resource efficiency.

For example, the online platform Global Forest Watch (GFW) uses AI to analyze satellite imagery to identify forest loss. Thousands of people use GFW every day to prevent illegal logging and forest fires. In addition, GFW helps countries implement national conservation programs.

In addition, AI technologies can synthesize new carbon-neutral materials and optimize production processes to reduce carbon emissions. For example, AI searches for chemical structures that have specific properties, such as the ability to absorb carbon dioxide or retain energy from sunlight.

Thus, AI gives us the answer to one of the global challenges facing humanity: how to maintain the development of production and at the same time reduce greenhouse gas emissions.

Agile Energy Management: AI for the Energy Transition

AI is a critical technology for the transition to clean energy, says Eurelectric study. It is expected that by 2025, 81% of energy companies in the world will implement artificial intelligence. The transition to renewable energy sources, which are characterized by instability, is also increasing interest in these technologies. Therefore, for their effective use, a flexible and decentralized system controlled by neural networks is required.

Experts surveyed by McKinsey also believe that AI will help make the most of solar, wind and hydropower. Algorithms can forecast generation and consumption volumes minute by minute, eliminate electricity losses and ensure the redirection of electricity to where it is needed at the moment. Thus, large green energy projects such as connecting solar and wind power plants in Morocco to the UK power grid via undersea cables could become a reality.

In addition, digital companies themselves, which use a lot of electricity, are reducing their carbon footprint with the help of AI. For example, the AIRI Institute of Artificial Intelligence, with the support of Sber, has developed the open Eco4cast library, which allows reducing CO 2 emissions by up to 90% when performing resource-intensive calculations, including when training neural networks on supercomputers.

And Google is using AI to save up to 40% on data center cooling energy. At first, the cooling system simply used artificial intelligence recommendations. But later, having assessed the effectiveness, all control was completely transferred to AI.

Typhoon monitoring and flood forecasting: AI for climate risk assessment
Artificial intelligence is a revolutionary technology in terms of assessing and analyzing climate risks, says Ecological Processes, because a neural network can provide more accurate forecasts and calculations of the consequences of extreme weather events.

For example, Sber created its own AI model for predicting climate risk events – fires, floods, storms, thawing of permafrost. According to the company, over the past 60 years, fires have become 6.5 times more common, heat and cold waves – ten times, floods – 12 times. The model automates the assessment of financial risks and helps farmers, industrialists and companies from other industries build a strategy for their development, taking into account forecasts. According to Sberbank’s Senior Vice President for ESG Tatyana Zavyalova, such an assessment of financial risks taking into account climate risks will reduce the bank’s losses to 1 billion rubles. in year.

Amur tigers, polar bears and drones in the Arctic: AI and biodiversity

According to the UN, about 1 million species of plants and animals are at risk of extinction, that is, approximately 25% of the entire living world. This highlights the urgent need to improve environmental measures. Artificial intelligence technologies can help here too.

Artificial intelligence opens up fundamentally new opportunities for studying and monitoring the state of flora and fauna. In particular, it will be much faster to process photographic data from drones and camera traps.

One of the solutions in this area is CAPTAIN (Conservation Area Prioritization Through Artificial Intelligence – AI for prioritizing conservation areas). It helps accurately model changes in biodiversity in a specific area due to human-induced factors such as construction. The CAPTAIN service allows you to protect on average 26% more species.

Another direction in this area is tracking rare animals that are in danger of extinction. Portland-based nonprofit Wild Me has developed a neural network model that recognizes zebras and giraffes by their patterns.

In Russia, they plan to use AI to recognize Amur tigers and to count the number of polar bears, walruses, polar gulls and wild reindeer in the Arctic using drones.

Sensors, housing and communal services and smart heat supply: AI for development and smart cities

The UN Economic Commission for Europe reports that cities, as the dominant form of organizing space and people’s lives, play a central role in sustainable development. On the other hand, urbanization also brings with it many problems that slow down the achievement of the SDGs.

For cities to become truly “smart” and sustainable, it is necessary to introduce AI, machine learning, the Internet of things and cloud solutions – the global expert community agrees. “Smart” solutions will allow you to effectively manage resources and reduce the negative impact on the environment.

One of the striking examples of a “smart” city is Oslo. By 2025, they plan to abandon all types of transport except electric ones, digitize all city and municipal services, equip all buildings with sensors, as well as energy and waste management systems based on AI.

In Russia, the Smart City concept is already being implemented in 213 cities with a population of over 100 thousand people. In particular, Rosatom is involved in the development of “smart” cities: the company is implementing AI in the housing and chemical sector to prevent accidents and reduce resource losses.

Sber, in turn, is building a new district in the west of Moscow according to the principles of a “smart” city – SberCity. One of the features of the quarter is a predictive energy management system.

“Smart” energy centers will be located on the upper floors of the buildings. Their special software will monitor the weather and the operation of various devices, such as ventilation systems and heating devices, in real time.

In this way, a comfortable temperature will be created in the houses, and resources will be spent rationally. SberCity also plans to widely use solar panels as facade material – the energy obtained in this way can cover up to 30% of general building needs. The project also provides for the installation of charging stations for electric cars in parking lots. AI will help manage all systems.

Education, medical diagnostics and targeted assistance: AI in the social sphere
The former head of DeepMind and one of the founders of Inflection AI, Mustafa Suleiman , is confident that artificial intelligence will become a tool for achieving social justice and equality thanks to “smart” solutions implemented in medicine, agriculture, as well as for the production of cheaper and more reliable building materials.

AI also has good prospects in the education segment, according to UNESCO. They note that technology makes knowledge more accessible and makes education more individual and of higher quality. AI is also useful as an assistive technology for teaching people with disabilities and health conditions. AI models help them with reading and writing, ensuring an inclusive learning environment.

Neural networks also open up new opportunities in healthcare – “smart” technologies assist surgeons and have learned to select the most effective treatment methods for patients. Various AI models are also being considered for the treatment of depression : they can record changes in the patient’s brain and identify areas that require attention.

And Sber has developed a comprehensive solution based on artificial intelligence that helps diagnose cases of cerebrovascular accidents and provide assistance to patients with stroke as quickly as possible. The service is already used in the Primorsky Territory and is being prepared for launch in the Novosibirsk region.

Finally, some social services are already using AI. For example, social workers in Pennsylvania are using predictive models to proactively provide assistance to families in need. As a result, the number of cases of deprivation of parental rights decreased by 47%.

The Evolution of AI for Sustainable Development

The interaction between artificial intelligence and the surrounding world is not one-way. In other words, it’s not just AI that is having an impact. It may also be the other way around: for example, neural network developers “look” for solutions from nature itself.

According to Semyon Budyonny, managing director, head of the development department for advanced AI technologies of Sberbank, AIRI scientific consultant, sustainable development and artificial intelligence are two large interdisciplinary areas of knowledge aimed at the future. And at the intersection of these two topics, more and more specialists are being cultivated who want to develop technologies to achieve sustainable development goals. Semyon Budyonny emphasizes that now is the time for AI, inspired by both the SDGs and the laws of nature.

For example, the area of ​​swarm intelligence (Swarm Intelligence) for the orchestration of multi-agent systems is developing quite actively. Algorithms are created inspired by the behavior of ants , fireflies and bats . Such models can be used in robotics, route planning and in various industries.

Evolutionary algorithms based on Darwin’s theory imitate the processes of natural selection of living organisms and are suitable for data analysis and process optimization. And artificial neural networks (Artificial Neural Networks), created according to the example of the work of the human brain and the interaction of neurons in it, make it possible to recognize and classify data with enormous speed.

Thus, it is no coincidence that at the world’s largest conference in the field of artificial intelligence, Artificial Intelligence Journey (AIJ), which will be held on November 22–24, a separate track will be devoted to the synergy of artificial intelligence and sustainable development. You can also learn more about how artificial intelligence helps create a sustainable future and creates new opportunities for humans in special podcasts on the AI ​​Journey conference website .

Humanoid robots and an AI mobile phone without a display: what happened in IT in May

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Funding for AI startups is declining, Palm Pay supports the trend to simplify payments, and clinical trials of neurochips on humans will begin in 2024

Glossary

Generative AI – Generative AI models are machine learning techniques that learn from content or objects and use them to create new data. They can be used to generate software codes, images and text, drug development, and as part of targeted marketing. Research firm Gartner estimates that generative AI will account for 10% of all data produced by 2025, up from less than 1% today .

Compliance  – (from the English compliance – “compliance with requirements”) – compliance on the part of a financial organization with special rules that allow it to remain within the framework of legal and legislative measures. This is done in order to ensure maximum legitimacy of the company’s activities.

The digest was prepared by the red_mad_robot analytical center.

Trends of the month: adaptation of humanoid robots, AI in Microsoft Build and a secret project from Humane

The growing popularity of humanoid robots. The development of human-like robots is a promising area of ​​technology development. Thus, the Figure startup, which is developing the Figure 01 robot, raised $70 million at the end of May. Tesla at the annual meeting of shareholders showed new prototypes of humanoid robots Tesla Bot. They will help people do different jobs, and in some areas they will even be able to replace them. It is planned that Tesla Bot will work on the production line of the Cybertruck electric pickup truck, will be able to generate a digital map of the area, and also interact with soft or fragile objects.

Tesla is not the first company to show a humanoid robot in 2023. OpenAI-backed startup 1X Technologies unveiled the EVE robot back in April , which is already working as a security guard at a factory. In addition, the robot can be a nurse or a bartender. EVE is equipped with cameras, security sensors and motion sensors.

Canadian startup Sanctuary AI introduced Phoenix humanoid robots. What makes this robot different is its complex and dexterous “human” hands. With them, he can lift up to 25 kg and perform a variety of tasks, including packaging, labeling and stacking goods.

Robots in catering. American fast food chain Wendy’s plans to use a chatbot based on Google’s artificial intelligence technologies to take orders. And robot carts will deliver them. At the same time, Wendy’s does not plan to replace humans with AI: employees will monitor its work and help customers as needed.

Neurochip testing . The FDA (Food and Drug Administration in the United States) has allowed the neurotechnology company Neuralink, founded by Elon Musk, to test neurochips on humans. The neurochip will be implanted into the brain and allow it to exchange information with an external device. According to Musk, testing will begin in 2023.

Paradromics’ Connexus Direct device, a Neuralink competitor, has been designated a Breakthrough Device by the FDA. This designation is given to medical devices that can improve the treatment or diagnosis of life-threatening diseases. The first human clinical trials will begin in the first half of 2024.

Funding for AI startups. According to the analytics company CB Insights, in the first quarter of 2023, investments in AI fell to $5.4 billion . This is 43% less than in the fourth quarter of 2022. In April, AI companies raised about $2.8 billion , second to the healthcare sector. Despite this, AI projects will raise mega-rounds (a fundraising round of $100 million or more): at the end of May, AI startup Anthropic (specializing in the development of language model systems) raised $450 million to create the next generation of AI assistants, and modular app creation platform Builder.ai raised another $250 million .

Neural network analogue of Photoshop. The DragGAN neural network allows users to edit an image by dragging its elements. The user marks two points with the mouse, moves them in different directions, and the objects in the image change. For example, the demonstration video showed how the animals changed their position or closed their eyes, and the girl updated her hairstyle. The rest of the space organically adapts to the changed elements.

Microsoft Build Embraces AI . The Copilot AI assistant will be integrated directly into the taskbar as a separate button. When you call the AI ​​assistant, a side panel will open, and you can ask Copilot, for example, what the weather is like today, where to go on the weekend, and find out the schedule of shows at the cinema. It is also known that Microsoft has already added Bing (a search engine from Microsoft) with AI integrated into it in the Windows 11 update.

Secret project . Humane, a startup from former Apple employees that produces cameras with artificial intelligence technologies integrated into them, presented a mobile device without a display, but with AI and a voice interface, at the TED conference . According to the creators, with the help of AI, the device is able to analyze the environment and, if necessary, project an image onto the desired surface.

Control is carried out using gestures and voice commands. During the speech, the Humane gadget was in the top manager’s jacket pocket and simultaneously translated his speech into French. The device can also make summaries of emails and meetings. Humane’s developments are carried out in complete secrecy. At the same time, the startup receives investments from LG, Microsoft, Volvo, Tiger Global and OpenAI.

Topic of the month: what is Palm Pay technology

Palm Pay  is a biometric payment method that works by recognizing palm prints and vein patterns.

In mid-May, the Chinese company Tencent introduced this method through its WeChat Pay service. The technology is being tested in the Beijing subway and in several retail stores in Shenzhen. The company will gradually introduce it in offices, university campuses, retail outlets and restaurants. Tencent hopes the product will simplify the consumer experience.

Who else is promoting palm payment: Amazon, JPMorgan, Fujitsu, PopID and Mastercard

Since 2020, Amazon has been developing Amazon One Checkout technology , which allows you to buy offline with your palm – to pay you need to put your palm on the Amazon One scanning device. The company said the technology will be used in more than 65 Whole Foods stores, as well as outside the Amazon ecosystem. It is already used in the chain of cafe-bakeries Panera Bread and Starbucks .

In May, the company announced that its technology detects age from the palm of your hand. This allows you to buy alcohol in stores, bars and stadiums without a passport. According to Amazon, the technology is currently only available at Coors Field in Denver.

JPMorgan is piloting biometrics technology in the US to let shoppers pay by scanning their palm or face. The bank believes that this will increase customer loyalty and lead to growth and acceleration of sales. If the pilot project is successful, then in 2024 the technology will be used in a large number of stores in the United States.

The Japanese corporation Fujitsu has been offering PalmSecure for ten years, but due to the high cost of the scanner, it has never rolled out the product en masse. This year, the company teamed up with card terminal manufacturer Ingenico, and together they developed technology that identifies a user and allows him to make payments based on his vein pattern.

Startups of the month: Worldcoin, Hadrius and Hands-In
Worldcoin – biometric identification with crypto wallet. The blockchain project of Sam Altman, CEO of OpenAI, focuses on creating three products:

Global digital currency Worldcoin.

Global identifier World ID . To obtain it, you need to scan your iris using a device called Orb. Users will be able to receive cryptocurrency for scanning.

World App , which allows you to pay, buy and make transfers using Worldcoin.

At the end of May, the project raised $115 million . The investors were the Blockchain Capital fund, Andreessen Horowitz and Bain Capital Crypto. The number of people registered in the Worldcoin project is approaching 2 million.

Hadrius is an AI assistant for compliance. Hadrius provides AI tools to automate the Securities and Exchange Commission (SEC) compliance process at financial companies – such as monitoring communications, marketing materials, risk assessment, etc. The startup uses GPT-3 and claims it can save about 90% of the time spent on routine work. According to Hadrius , more than 30,000 financial institutions face multibillion-dollar costs to continually comply with SEC regulations, and as regulations become more stringent each year, those costs continue to rise.

Hands-In – Buy Now, Pay Together (BNPT). The UK startup provides software and technology infrastructure where one or more customers can pay for a product or service by splitting the cost among themselves.

The product integrates with the existing infrastructure for accepting acquiring and payments. Hands-In is designed to solve the problem of buying expensive goods – in the current economic conditions, not everyone can afford to pay for the purchase in full. In mid-May, the company raised $550 thousand . Investors include fintech companies GoCardless, Thredd, Elavon, FIS, PayU, Curve and Free Trade. Hands-In intends to use the investment to accelerate the commercialization of services.

Medical robot operator: who is he and what does he do?

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In the future, robots will replace humans in many fields. At the same time, new professions will appear. One of these is a medical robot operator. We tell you what he will do, what he should be able to do and how to become one.

Who is a medical robot operator?

A medical robot operator  is a specialist who programs, configures diagnostic, therapeutic, surgical and other robots that help doctors carry out various procedures, and also knows how to control them.

Robotic devices are used in medicine at all stages of treatment. They diagnose patients, perform surgeries, help patients follow doctor’s orders, and assist medical staff with tasks ranging from preparing instruments to applying sutures.

What does a medical robot operator do?

The medical robot operator is responsible for the smooth functioning of the medical robots. He accompanies the robot at all stages of its life – from programming and internal settings to its maintenance and diagnostics of the quality of work.

His tasks include:

  • monitoring the general condition of the robot based on information from built-in sensors;
  • operating system performance assessment;
  • building models and predicting the robot’s activity at work;
  • planning the robot’s actions in accordance with the tasks;
  • writing program code for the robot and loading it into the device;
    robot maintenance.

Basic Skills for a Medical Robot Operator

A specialist in this field must be technically savvy and understand :

  • mathematics;
  • computer science;
  • basics of electronics;
  • mechanics;
  • software operation;

robotics.

In addition, he needs to be able to program, understand the principles of artificial intelligence, and also speak English at a high level. Medical robots are not yet produced in Russia, so a foreign language is needed to translate instructions and undergo training with the robot.

Trends and directions of the profession

Medical robots are a promising area of ​​robotics. In the HSE ISSEK ranking “Top 15 Robotics Trends,” robotic surgery took fifth place. According to GlobeNewswire, the global medical robotics market was worth $10.88 billion in 2021. It is expected to reach $44.45 billion by 2030.

There are several types of medical robots:

  • sick leave,
  • social,
  • rehabilitation,
  • laboratory,
  • robots for radiation therapy,
  • robotic prosthetics,

robot surgeons.

The autonomy of the devices depends on the proximity of the work with the patient. For example, a surgical robot is completely controlled by a person, while hospital workers can independently perform various tasks – delivering food and medicine and sanitizing premises.

Where did the profession come from?

Medical robots began to develop in the second half of the 20th century. In 1985, using the Programmable Universal Manipulation Arm (PUMA) system, surgeons performed a puncture biopsy of the brain. In 1988, they developed the Probot system for transurethral resection of the prostate – removal of the entire organ or part of it in case of problems with urination. Then devices for joint prosthetics, neurosurgery, and radiation therapy appeared. In 1994, Computer Motion introduced the first robotic surgeon to receive FDA (Food and Drug Administration) certification.

In 1999, a successful operation was performed by the Da Vinci robotic surgeon . Today it is one of the most advanced robotic medical systems, which performs complex operations such as gastric bypass, mitral valve repair, and mediastinal tumor resection. The robot is controlled by a surgeon who observes the operated area through cameras with multiple magnification in 3D format and controls the robot’s actions using joysticks.

There are more and more medical robots every year. Statista calculated that in 2016 there were 713 of them, in 2017 there were already 826, and in 2025 there will be 2112 robots. For robots to function properly, a medical robot operator is needed.

How to become a medical robot operator

You can get a basic technical or medical higher education. In addition, such programs as “Mechatronics and Robotics” at the National Research University MPEI, “Biotechnical Systems and Technologies” at MIREA, “Digital Medicine and Bioinformatics” at the Ural Federal University named after the first President of Russia B.N. are being implemented in Russia. Yeltsin, “Medical Cybernetics” at the Russian National Research Medical University named after N.I. Pirogov.

Spot Transforms into an Artificial Intelligence Supported Tour Guide with ChatGPT Integration

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With an innovative combination of robotics and artificial intelligence, Boston Dynamics has reimagined four-legged mechanical wonder Spot as a charismatic tour guide.

Armed with the power of OpenAI’s ChatGPT and other large language models (LLMs), Spot has been transformed from an audit assistant into an interactive robot that can chat, answer questions, and offer tours with a touch of fun and nuance.

This evolution in Spot’s capabilities is a result of Boston Dynamics exploring the broad potential of foundational models—complex AI systems that are trained on extensive data sets and can exhibit emergent behavior.

Contents
From Control to InteractionTechnical crewEmerging BehaviorsHuman TouchChallenges and Prospects

From Control to Interaction

Previously known for his inspection skills, Spot now gains new abilities as he wanders the halls of Boston Dynamics. Equipped with an array of sensors and AI-powered speech and text recognition tools, Spot demonstrates a remarkable ability to interact with people in real time. This interaction isn’t just about presenting dry facts; it’s about creating an engaging, informative experience that may include some impromptu role-playing and even humor.

Technical crew

This transformation required Spot to be equipped with a vibration-resistant speaker housing to project its new sound. Controlled by an external computer using Spot SDK, the robot integrates OpenAI’s ChatGPT API upgraded to GPT-4 and various open source LLMs. Spot’s tour guide persona is also enhanced by visual question-answering patterns that allow him to identify objects he “sees” with his cameras and answer questions about them.

Emerging Behaviors

Spot’s interactions during the tours revealed unexpected behavior, such as independently asking for help or identifying ‘parents’ among older robot models. While the Boston Dynamics team is quick to clarify that this doesn’t mean LLMs are conscious or intelligent in a human-like way, these actions highlight AI’s capacity to make statistical associations and adapt to new contexts.

Human Touch

To contribute to Spot’s human-like interactions, the team used text-to-speech services and programmed body language into the robot, allowing its robotic arm to turn towards people and ‘talk’ to them by mimicking the movements of a human mouth.

Challenges and Prospects

Despite the successes, the team also acknowledges limitations, such as the LLM’s tendency to fabricate answers or the awkwardness of delayed answers. However, the team is optimistic about the future, envisioning a world where robots understand and act on verbal instructions, reducing the learning curve for human users and increasing the utility of robots in a variety of fields.

Spot’s new role as a tour guide represents a significant step in the ongoing convergence of artificial intelligence and robotics. It highlights the potential of these technologies to provide not only functional benefits, but also cultural context and a whimsical touch to our interactions with machines. The experience gained from this proof of concept promises to pave the way for even more sophisticated and seamless human-robot collaborations in the future.

The role of artificial intelligence in SEO: How is Machine Learning changing the game?

Need to explore the role of AI in SEO? So keep reading more.

Search engine optimization (SEO) is an important part of digital marketing that aims to optimize website content to gain greater visibility on search engine results pages. Of course it doesn’t stay in place.

Over the last few years, the strategies used in SEO have evolved significantly, particularly due to the emergence of artificial intelligence (AI) and machine learning (ML), both of which have changed the way search engines now rank websites.

So, in such an evolving world, the only way to succeed and remain competitive in the SEO landscape is to leverage AI and ML algorithms. In this article, I will examine the role of artificial intelligence in SEO, how it is used today, and its potential in the future.

I will also look at how businesses can leverage this technology to improve their search engine rankings and drive more traffic to their websites. Let’s get straight to the point!

What is artificial intelligence?

The role of artificial intelligence in SEO

Before going further, let’s understand what artificial intelligence is. You’ve probably heard of tools like:  ChatGPT  , ZebraCat, PercyLab, and others. All of these tools are AI-powered, giving them the ability to understand human-submitted queries with exemplary accuracy.

Now let’s move on to the topic of artificial intelligence. Essentially, it is the ability of machines to perform tasks that would normally require the involvement of a human; these include:

  • Seeing things;
  • Recognizes voice commands;
  • To make decisions;
  • Translate languages ​​and much more.

This technology is not new, but it has become quite widespread in recent years. In addition, today artificial intelligence is constantly trained due to the emergence of machine learning, which allows it to easily analyze large volumes of data, recognize behavioral patterns and make predictions based on recovered data.

Artificial intelligence, machine learning and SEO

But with the rise of Big Data, businesses began to realize the potential of machine learning to solve complex problems and gain insights from large data sets. This has led to the development of new machine learning techniques and the creation of specialized tools and frameworks that make it easier to build and deploy machine learning models.

Now  machine learning in finance  Its ability to handle complex financial data analysis makes it a valuable tool for risk assessment and fraud detection. Additionally, in education, artificial intelligence provides opportunities for personalized learning experiences, while in healthcare, these technologies contribute to advances in diagnosis and treatments.

What about SEO? 

AI and ML are now transforming SEO by providing more advanced and effective strategies to help improve search engine rankings, increase your website traffic, and improve user experience. Here are some of the ways AI and ML achieve this:

  • Better search relevance.
  • Personalized search results.
  • Voice call.
  • Natural language processing.
  • Content optimization.
  • Searching for pictures and videos.

Let’s take a closer look at each.

Content optimization

Artificial intelligence and machine learning are also widely used to analyze content, including its structure, use of certain words, accuracy of information, punctuation and spelling. This factor should be taken into account when optimizing content for search engines.

For example, when your content revolves around  IoT healthcare solutions , it is crucial to ensure that it is highly informative and targets an advanced audience looking for in-depth information about the product and related topics.

Writers and experts face challenges when creating content on such topics as it must appeal to both the target audience and the search engine. Various AI SEO tools and AI SEO friendly copywriters simplify this task several times.

Additionally, some services use artificial intelligence and machine learning technologies to improve the quality and reliability of academic content. These services use advanced algorithms to perform comprehensive literature reviews, analyze data, and generate accurate citations.

Using research paper writing services students and researchers can save time, ensure the accuracy of their work, and get valuable opinions from experienced professionals in their field.

Better search relevance

Search engines use algorithms to analyze millions of web pages and provide users with the most relevant results. But while in the past they relied solely on factors like keyword density, meta tags, and backlinks, today they use advanced machine learning algorithms that allow them to understand the intent behind each request.

In practice, this means that simply stuffing content with keywords, as spammers did a decade ago, is not enough to rank higher in search results. For the Google RankBrain algorithm to identify a resource as useful and relevant, the resource must contain meaningful content that matches the user’s search query, even if no exact keywords are used.

Personalized search results

With the help of AI and ML, search engines can now deliver personalized search results based on the user’s search history, location, and preferences. For example, if multiple people use the same keyword when searching the internet, the search results will never be the same.

For SEO experts, this means two things:

  • There is no longer a single “best” outcome;
  • Strategies should be created based on  target audience segments and interests  and not just based on the use of keywords.

Voice call

The rise of advanced voice assistants such as Siri, Alexa, and Google Assistant has now changed the way people search for information. According to Adobe research, 48% of adults surveyed in the United States admitted to using voice for general web searches.

Artificial intelligence and machine learning algorithms are used to improve speech recognition and natural language processing; This means SEO strategies should be optimized for voice search queries.

Challenge? Since people often use conversational queries during voice search, optimizing content with short keywords is no longer enough. It has become necessary to include long-tail keywords to increase the ranking of a site.

Many long-tail keywords, for example “  How to buy Ripple in India  ”, are identified by the number of words they contain. It is fake. It all depends on the search volume. However, some short-tail keywords, unlike those consisting of five words (or more), have a monthly search count less (<100).These keywords can receive thousands of searches each month.

Apart from this, voice search is often used to identify nearby services and businesses, so it is important to consider local search results when developing an SEO strategy.

Natural language processing

Natural language processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and human language. With the help of NLP, search engines can now understand the context and intent of a query; This means SEO professionals should create their strategies with semantic search in mind.

To give you an idea, initially Google algorithms only used keywords to decide whether content was relevant or not. Now with AI and ML, they understand the context of a written article based on the words and phrases before and after keywords, as well as the subtleties of a query, allowing them to rank shorter and more relevant websites higher.

If you want to optimize chatbot integration and get the best results, hire  Node.js developers. This allows you to leverage the power of Node.js to deliver great user experiences and enhance the functionality of your chatbot system.

Image and video search

Another area that is transforming thanks to the integration of artificial intelligence and machine learning is visual and video search. It hasn’t been that long since tools like Pinterest Lens and Google Lens appeared, but it’s already pretty clear that the trend of using visual and video search to find information online is very strong.

With this in mind, SEO professionals make use of alt tags, metadata, descriptive filenames, etc. to help search engines understand their context and match them with relevant search queries. should optimize their visual content, including the use of

Opportunities for businesses to leverage AI and machine learning for SEO

The role of artificial intelligence in SEO

Now that we’ve covered the SEO areas most impacted by the rise of AI and ML, let’s take a look at how businesses can leverage these technologies to improve their SEO strategies and gain a competitive advantage.

In general, SEO strategies should be created focusing on the following:

  • User purpose;
  • Use of long-tail keywords;
  • Local SEO;
  • Visual search;
  • Performance analysis.

You can find more information about each below.

User intent

By integrating artificial intelligence and machine learning, search engines can now understand the intent of a user query, making it necessary to create an SEO strategy based on user needs.

To put this into practice, first conduct extensive keyword research to make sure you understand the user’s intent behind a search query. Based on this information, create content that meets this goal and also provides information that is valuable to them.

Use long-tail keywords

With the popularity of voice searches, it has become necessary to optimize content with long-tail keywords that sound as natural as possible in the language people use when searching online.

When chosen correctly, long-tail keywords help you get more traffic by targeting the right audience, making their use a must-have in an SEO strategy.

For example, users can provide information and analysis on “  et prediction  ”, Ethereum price predictions. Stay up to date with the latest market trends and analysis to provide accurate and reliable information to your audience.

Local SEO

As more people use voice search to find information online, local SEO cannot be neglected. If you haven’t yet optimized your Google My Business profile and added local business listings, now is the time to do it. Otherwise, you’ll lose a lot of local traffic.

image search

As we mentioned before, visual search is another popular way to find information online. With this in mind, whatever type of visual content you have on a website, make sure it is fully optimized for search engines and includes alt tags, meta descriptions, titles, etc. It’s important to make sure it’s included.

It goes without saying that your content should also be visually appealing and relevant to user search queries. If it isn’t, there’s no point in publishing it in the first place.

Performance analysis

Finally, it is important to track and analyze the results of SEO efforts to ensure the success of an SEO campaign. Without monitoring and analysis, you won’t know what works and what doesn’t; This can lead to waste of time and resources.

Therefore, the first step is to create analytics. Google Analytics is a popular choice and can provide valuable insight into your website and user behavior patterns.

Once you’re done, you’ll need to keep a close eye on your rankings. To do this, you can use analysis tools such as:

  • Semrush
  • SEO Power Pack

The one that suits you best.

Of course, you also need to know the volume of traffic and conversions you’re getting. By measuring these KPIs, you get an idea about the impact of your SEO efforts on users and whether they meet your expectations.

Then analyze your content. Look at your page’s click-through rates (CTR) to understand how it’s performing in search engines and identify opportunities to optimize your content for search engines.

Finally, check your backlink profile. By doing this, you will not only learn how your website is performing, but you will also be able to identify opportunities to get new backlinks from authoritative websites.

FAQ on the Role of Artificial Intelligence in SEO

How can artificial intelligence help SEO optimization?

Using AI-based analytics tools like Insights  streamlines the SEO action item evaluation process  . Rather than reviewing multiple reports, AI technologies can find patterns and realize the benefit of targeting one keyword over another.

Why is artificial influence important for SEO?

AI-powered tools can analyze user behavior and provide personalized recommendations to improve website usability, loading times, and other factors that affect technical SEO . But these are just a few examples of how AI impacts SEO

How to use artificial intelligence and machine learning in SEO?

SEO AI is the use of artificial intelligence-based technologies to help improve website SEO.
This implies  analyzing data and using machine learning (ML) algorithms to determine the best keywords, content structure, and other factors that help a website rank higher on the SERP

What are popular AI tools for keyword research?

Some of the commonly used AI-based keyword research tools include SEMrush, Ahrefs, and Google’s Keyword Planner.

Can AI really improve the quality of my content?

Absolument.
AI tools can analyze your content for readability, suggest improvements, and even create high-quality content. This ultimately improves the overall quality of your content.

How does artificial intelligence predict user behavior?

Artificial intelligence uses advanced algorithms and data analysis to identify patterns in user behavior. This data-driven approach allows you to effectively tailor your content to meet user needs and preferences.

Are there free AI tools for content optimization?

Yes, some AI-powered content optimization tools offer free versions with basic features. Examples include Grammarly and Yoast SEO

Why is voice search optimization important?

With the proliferation of voice-activated devices and voice assistants like Siri and Alexa, voice search optimization ensures your content remains accessible and relevant to a wider audience.

What is the best use or example of AI in SEO and marketing?

Artificial intelligence can be used in marketing  personalization, predictive analysis  , content writing, video production, competitive intelligence, social media marketing, advertising, etc.

Will artificial intelligence replace SEO?

Artificial Intelligence Could Change How SEO is Done, But  It’s Unlikely to Replace the Entire Profession . While AI can automate certain aspects of SEO, such as keyword analysis and technical site audits, it still requires human expertise and creativity to develop and implement effective strategies.

How will artificial intelligence change websites?

One of the most important ways AI is changing websites is  through the use of natural language processing (NLP) and machine learning (ML) technologies  .
NLP allows machines to understand and interpret human language, making it easier for users to find information using natural language queries.

How does AI help Google Search?

The main way search engines use artificial intelligence  is to rank web pages, videos, and other content in search results . Google (and other search engines) rely on sophisticated artificial intelligence to determine how to rank content.

What are the limits of artificial intelligence in SEO?

Limitations of AI-Generated Content for SEO: Can extract inaccurate, unreliable, or even biased information  . In the same vein, artificial intelligence models are also based on limited data.
For example, ChatGPT is limited to pre-2021 data

How to use artificial intelligence for SEO keyword research?

Use AI Keyword Generator for Keyword Research
Step 1: Conduct a keyword search using a reliable AI keyword generator.
Step 2: Check the search data in Google Keyword Planner.
Step 3: Create an SEO summary.
Step 4: Optimize Content for SEO Success.

Conclusion

To summarize, as search engines evolve and improve, the role of artificial intelligence and machine learning in SEO continues to grow. Artificial intelligence and machine learning algorithms can analyze large volumes of data, recognize patterns and trends, and make more informed decisions about strategies.

But this does not mean that human participation is no longer necessary. SEO experts still play a vital role in analyzing data, interpreting results, and making strategic decisions. So if you want to run a successful SEO campaign and maintain your competitive advantage, the best thing to do is to combine the two: Leverage the power of AI, ML, and human expertise.