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OpenAI and Meta signaled this week that they will soon release new AI models they say will be capable of reasoning and planning, critical steps towards achieving superhuman cognition in machines. Things are moving so fast that the capability of new artificial intelligence models may surpass human intelligence by the end of next year, Elon Musk, founder of Tesla and SpaceX, said April 28 in an interview with Nicolai Tangen, CEO of Norges Bank Investment Management, Norway’s $1.6 trillion sovereign fund and one of the largest investors in Tesla.

While not all AI experts agree on that timeline, it is now a given that every organization will need to adopt the technology. Jamie Dimon, chief executive of JPMorgan Chase told investors April 8 that AI could be as transformative as some of the major technological inventions over the past several hundred years. “Think the printing press, the steam engine, electricity, computing and the Internet, among others,” Dimon wrote in his annual letter to shareholders. “We have been actively using predictive AI and ML for years — and now have over 400 use cases in production in areas such as marketing, fraud and risk — and they are increasingly driving real business value across our businesses and functions,” Dimon said in the newsletter. “We're also exploring the potential that generative AI (GenAI) can unlock across a range of domains, most notably in software engineering, customer service and operations, as well as in general employee productivity.”

But as both tech companies and corporates in traditional businesses race to deploy the technology the increasing power of the latest AI systems is stretching traditional evaluation methods to the breaking point, posing a challenge over how to safely work with the fast-evolving technology, The Financial Times reported this week. The problem of how to assess LLMs has shifted from academia to the boardroom, as generative AI has become the top investment priority of 70 % of chief executives, according to a KPMG survey of more than 1,300 global CEOs.

Against that backdrop some 1,500 global leader and Generative AI pioneers gathered in Paris April 8 for the R.AI.SE Summit (pictured here) to share first-hand insights on using Generative AI to address essential business and societal challenges. Read on to get the key takeaways from the conference and the week's most important technology news impacting business.

Seeing Responsible AI as a cost of doing business is the wrong way to view it. With falling levels of trust in AI products and the companies creating and using it, creating products with responsible AI will add to the bottom line and success with customers, Kay Firth-Butterfield, one of the world’s foremost experts on AI governance, says in her second exclusive column for The Innovator. Kay is the founder and CEO of Good Tech Advisory.. Until recently she was Head of Artificial Intelligence and a member of the Executive Committee at the World Economic Forum. In February she won The Time100 Impact Award for her work on responsible AI governance. Firth-Butterfield is a barrister, former judge and professor, technologist and entrepreneur and Vice-Chair of The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence And Autonomous Systems. She regularly speaks to international audiences addressing many aspects of the beneficial and challenging technical, economic, and social changes arising from the use of AI.

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Hirundo, which splits its headquarters between Tel Aviv and London, is building a Machine Unlearning Platform to ensure that AI models only know what they should. The company is a pioneer in a nascent field that focuses on making AI forget.

Until now training AI models has been a one-way track: The only way to remove unwanted data that has entered the model is to retrain the model, a lengthy and expensive process

Hirundo removes the unwanted data from the model, at less than 5% of the time and the cost to retrain, says CEO Ben Luria, a keynote speaker at the April 8 R.AI.SE conference in Paris, which focused on Generative AI. “We are like a precision knife that does surgery,” he says.

Every company using AI will inevitably find inaccurate data, bias caused by things that should not be considered such as gender, noncompliant or poisoned data, says Luria, an experienced entrepreneur and one of Israel’s first Rhodes scholar. Copyright laws and privacy regulations that give people the "right to be forgotten," are also driving interest in techniques that can remove traces of data from algorithms without interfering with the model's performance.

But unlearning isn’t as straightforward as learning. It "remains one of the most challenging conundrums in the AI sphere,” Microsoft wrote in a paper published in October.

Along with Hirundo, Microsoft and researchers are trying to rise to the challenge.

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Number of deep tech scale-ups that gathered in Brussels April 9-10 for an Ignition Forum event organized by the EIC Scaling Club, a new curated community that includes investors, corporate innovators and other industry stakeholders. (The Innovator’s Editor-in-Chief Jennifer L. Schenker is on the advisory board of The EIC Scaling Club, an arm of The European Innovation Council). The chosen companies fit into four market categories: Digital Security & Trust, Next-Gen Computing, Smart Mobility and Renewable Energies. The scale-ups – which include one that uses AI to help trains run on time and another that helps grid operators send 30% to 40% more electricity over existing power lines - were chosen for their ability to change industries.