Near Lausanne, Switzerland, Ioannis Ieridesbusiness development manager at Iprovastrives to demonstrate the value of its company in the innovation economy. The objective? Illustrate how artificial intelligence (AI) can transform invention processes.

A revolutionary invention process

Iprova specializes in selling invention ideas, combining human creativity and advanced technology. When a client signs a contract, Iprova begins submitting proposals for patentable inventions tailored to their industry. Although all patents are attributed to human inventors, they benefit from the AI ​​tools developed by Iprova.

The key role of their software is to explore both relevant data from the client’s business domain and related fields to suggest innovative inventions. By collaborating with renowned companies such as Procter & Gamble, Deutsche TelekomAnd PanasonicIprova has established itself as a key player in the innovation sector.

How Iprova optimizes creativity

During a demonstration, Iérides wanted to prove how Iprova could accelerate the creation of inventions. Using the software, he was able to search through thousands of documents, including patents and scientific publications. Here’s a look at the steps he took:

• Framing Step: The software generates a pie chart illustrating relevant research areas.
• Detection and Connection: The tool provides text summaries and suggests relationships between ideas.
• Generation of Invention: An invention proposal is formulated, combining technological advances and market needs.

For example, when searching for a automatic transcriberIprova suggested a system using advanced microphones combined with speaker identification software. This approach highlights the immense potential for innovation offered by AI.

Panasonic’s Memorable Experience

Another striking example is the collaboration with Panasonic. The company sought help from Iprova to exploit the potential of autonomous vehicles. The software came up with an innovative idea: using cars for delivery missions when their passengers are not on board. This bold suggestion led Panasonic to file a patent in 2021, highlighting Iprova’s ability to generate forward-thinking ideas.

An invention strategy based on AI

The co-founder and CEO of Iprova, Julien Nolanemphasizes the importance of convincing customers of the relevance of Iprova’s solutions. According to him, in the field of invention, success is often decided a few months in advance. By combining in-depth literature analysis and knowledge of market needs, Iprova helps businesses stay ahead of the competition.

Exploitation of the Iprova index

Iprova has developed a Indexa dataset of recent and relevant inventions. This tool helps quickly identify signals of novelty in specific areas. By examining this index, Iprova engineers can reveal opportunities for inventions

Invention in the Age of Information Overload

No engineer, no matter how well educated, can be an expert in every potentially useful field. At an industry meeting hosted by Iprova in June, Cronin explained how difficult it was becoming for engineers to comply with all telecommunications standards. A pacemaker that can connect to a 5G network must comply with both health and telecoms standards. A drone must also meet aviation requirements. As the Internet’s wireless tentacles extend to more and more devices, telecommunications engineers can’t follow all the rules.

Iprova found the problem of proliferating telecommunications standards so appealing that it built a module for its software to track so-called industry standards. 3GPP standards and help inventors make new 3GPP-compatible inventions. The tool can break through the “jargon wall” of the original normative texts, Cronin said, and identify useful similarities.

Bonabeau’s company, Biomedit, is doing something similar to invent new peptides using AlphaFold, DeepMind’s biology-focused generative AI tool. Bonabeau says the generative component has revolutionized his company’s workflow, allowing Biomedit to identify effective peptides while synthesizing thousands fewer candidates. Generative AI is “integrated into our process,” he says.

Iprova’s approach differs because it focuses on physical rather than biological inventions. A biological invention is like a hypothesis – it requires a wet lab and time to confirm that it works – while a physical invention is more like a mathematical proof. The inventor, the customer, and, in final testing, a patent examiner, should all be able to see the novelty and value of the textual description.

In a world where artificial intelligence (AI) is progressing by leaps and bounds, one question remains: what is the place of humans in the invention process? Experts like Nolan and Bonabeau explore this theme through revealing analogies and observations about how AI works.

The machine and human intuition

Nolan often uses a culinary analogy to illustrate the complementarity between AI and humans. He says while a machine can suggest unfamiliar ingredients to a cook, the perfect combination relies on human intuition. Bonabeau shares this vision, affirming that the presence of humans in the invention circuit is essential. He points out that AI, although it can analyze information, cannot not judge the interest of an invention or idea. This limitation highlights a crucial weakness: the machine lacks the nuanced understanding that only humans possess.

The role of humans in the invention process

Researchers like Paul Sagel of Procter & Gamble also confirm this necessity of human intuition in the creative process. At a recent innovation meeting hosted by Iprova, he said: “AI really can’t invent. There must be an element of human assistance…otherwise she’s hallucinating. » This observation highlights the shared responsibility between AI and humans to generate innovative ideas.

Thoughts on AI-assisted invention

While some skepticism persists, researchers like Thaler and Abbott are working to establish legal grounds for granting patents to AI systems. At the same time, inventors are exploring various ways to use AI, paving the way for unexpected results. Nolan, for example, presented the idea of ​​offering a predictable number of inventions each week, as well as exploiting chance to generate ideas. According to him, these “ Eureka moments » programmed can be beneficial for customers, promoting a proactive approach to innovation.

The allure of the unknown in generative AI

For Bonabeau, the chaotic aspect of AI-assisted invention is valuable. He considers the “ hallucinations » of AI as an invaluable source of innovation, comparing this process to a “ mushroom trip“, where unexpected associations can lead to surprising discoveries. This approach suggests a horizon where innovation is not only a question of logic, but also of creativity and surprises.

Pattern recognition and collective intelligence

Much of what we define as AI relies on advanced pattern recognition. This includes analyzing the inventions of others. Nolan says that with enough examples, an AI can imitate the style of an inventor, just as a painter can reproduce the style of a master. From this perspective, companies, made up of groups of people, have their own collective models identifiable. An intelligent AI, led by an informed human, could thus detect these patterns within patent filings.

Anticipate competitor movements

This strategic use of AI could make it possible not only to design inventions, but also to anticipate the movements of competitors on the market. However, the question arises: what if these competitors also use AI to generate inventions? In this new era, it could happen that an AI predicts the next creation of another AI, making the race for innovation a real one. technological chess game.

In short, the collaboration between human intelligence and AI opens up fascinating perspectives. This interaction could redefine the boundaries of humanity and machine in the realm of invention, while preserving the very essence of human creativity.