How AI is fostering the birth of new technologies | AI in business #80

How can artificial intelligence contribute to the creation of new technologies?

Artificial intelligence is not only a fascinating new technology but also a powerful tool for creating innovative technological solutions. How can AI contribute to this?

1. Generating new ideas and concepts. AI helps to invent entirely new technologies and prototypes of devices. Artificial intelligence can combine facts and concepts in an unconventional way, finding solutions that may elude the human mind.
2. Testing and improving prototypes. Thanks to computer simulations, it is possible to quickly and inexpensively test the functionality of a prototype, without wasting time and money on building physical models. AI also allows modeling various usage scenarios and optimizing the project for specific goals.
3. Supporting the production process. Intelligent systems can analyze production data in real-time, detect abnormalities, and suggest modifications to processes, ensuring higher efficiency, lower failure rates, and better quality control.
4. Improving technology management. AI facilitates monitoring of technological systems, diagnosing and solving problems without human intervention. This saves time and resources, and the new technology operates more efficiently.

Source: DALL·E 3, prompt: Marta M. Kania (https://www.linkedin.com/in/martamatyldakania/)

AI programming: GitHub Copilot

One of the most interesting examples of using AI to assist programmers is GitHub Copilot (https://github.com/features/copilot). It is a tool based on advanced language models that “codes collaboratively” with humans.

However, how does GitHub Copilot work? Copilot analyzes the code written by the programmer and uses it as a reference. This allows it to suggest what should be found in the next lines of the program. It is capable of:

• suggesting expressions and even entire functions,
• generating code for algorithms based solely on the description,
• creating documentation based on the code itself,
• explaining code,
• proposing corrections,
• engaging in complex discussions with the programmer,
• and much more, all in dozens of popular programming languages.

Source: Github (https://github.com/features/copilot)

All a developer has to do is start writing a code snippet, and GitHub Copilot will suggest a complete proposal, based on the analysis of millions of public repositories and a deep understanding of the semantics of programming languages.

The main benefits for programmers include:

• speeding up work by up to 55%,
• increased productivity and satisfaction thanks to quickly emerging, effective solutions,
• less frustration when creating repetitive code,
• faster problem-solving.

Cloud new technologies: innovations from Microsoft

Microsoft has developed innovative applications of natural language models to address a common challenge for many cloud-using companies – issues related to managing such complex infrastructure and responding quickly to failures.

How was this achieved? Microsoft specialists utilized the capabilities of language models to analyze incident descriptions and logs. Based on this, the models can suggest the most likely causes of problems and optimal solutions.

Importantly, the more data fed into artificial intelligence, the more accurate it becomes at detecting and classifying new faults, resulting in faster response times and reduced losses due to cloud disruptions.

Using AI in automatic cloud incident management presents an opportunity for:

• faster diagnosis of the causes of failures – AI analyzes data faster than a human,
• automated repairs – artificial intelligence-generated solutions eliminate the need for human intervention
• less downtime and better operational continuity – faster response reduces losses for companies using new cloud technologies.

This is just the beginning of using AI in new cloud computing technologies. Soon, perhaps, the majority of administrative processes and technical support may be automated.

Siemens: testing software with AI

Siemens specialists have utilized machine learning capabilities to automate a very time-consuming aspect of software development – testing.

They developed a system of new technologies that, based on data from previous tests and code versions, can predict the results of new tests with 78% accuracy.

What does this give in practice? The most important aspect is faster feedback for developers. Developers receive preliminary suggestions regarding test results almost instantly, without waiting for the actual completion of tests, which in large projects can take hours or days.

This allows for faster identification and elimination of errors, without wasting time on context switching and recalling details of previously written code.

The second significant aspect is the optimization of the test order. Predictions regarding their results allow for determining the optimal sequence for running individual tests to encounter potential errors as quickly as possible.

This saves computational resources needed to perform a full set of tests. In studies, even a 10% reduction in the total testing time was observed.

Summary: new AI technologies

Artificial intelligence drives technological progress in many ways. It primarily:

• generates new ideas and device concepts by combining facts in unconventional ways,
• facilitates rapid and cost-effective prototyping, as well as expedites the solution testing process,
• optimizes design and production processes,
• automates the monitoring and maintenance of systems,
• speeds up the work of programmers,
• assists in diagnosing technical problems, and
• automates software testing.

Perhaps soon, the majority of groundbreaking inventions will emerge with the support of artificial intelligence. Therefore, it’s worth keeping abreast of these fascinating changes and continuously learning to leverage new technologies in your work.

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