Silicon Valley is bullish on AI agents. OpenAI CEO Sam Altman said agents will 'join the workforce' this year. Microsoft CEO Satya Nadella predicted that agents will replace certain knowledge work. Salesforce CEO Marc Benioff said that Salesforce's goal is to be 'the number one provider of digital labor in the world' via the company's various 'agentic' services. In the last few years, the tech industry has boldly proclaimed that AI 'agents' ' the latest buzzword ' are going to change everything. In the same way that AI chatbots like OpenAI's ChatGPT gave us new ways to surface information, agents will fundamentally change how we approach work, claim CEOs like Altman and Nadella. That may be true. But it also depends on how one defines 'agents,' which is no easy task. Much like other AI-related jargon (e.g. 'multimodal,' 'AGI,' and 'AI' itself), the terms 'agent' and 'agentic' are becoming diluted to the point of meaninglessness. That threatens to leave OpenAI, Microsoft, Salesforce, Amazon, Google, and the countless other companies building entire product lineups around agents in an awkward place. An agent from Amazon isn't the same as an agent from Google or any other vendor, and that's leading to confusion ' and customer frustration....

Poolside co-founder and CEO Jason Warner didn't mince words: He thinks that most companies looking to build foundation AI models should instead focus on building applications. Poolside is an AI-powered software development platform. Warner told the audience at the HumanX AI conference in Las Vegas on Monday that he thinks intelligence is the most important commodity in the world ' on par with electricity ' and anyone who doesn't believe this should not be building a foundation model. 'If you're one of those people, if you want to take one side of the fence, you're a printing press for cash unlike anything we've ever seen in the world,' Warner said. 'Or if the other side of the fence, you're basically changing and bending the arc of humanity in a way that we've not done before. And I believe that to be true.' Warner added that his company is 'literally' going after AGI through software. If someone looks at foundational models as more of a 'nice to have' as a way to raise VC cash, the company should just build a wrapper on an existing foundational model instead, he added....

While the improvements feel as incremental as its name suggests, GPT-4.5 is still OpenAI's most ambitious drop to date. Released in late February as a research preview'which essentially means OpenAI sees this as a beta version'GPT-4.5 uses more computing power than its previous models and was trained on more data. So, just how big is the GPT-4.5 research preview' Who knows'since the developers won't say. And where did this additional training data come from' Their lips are zipped on that as well. To borrow a line from Apple TV's hit show Severance, right now OpenAI is positioning the alleged improvements in this new model as mysterious and important. When comparing AI benchmark tests from competitors' models as well as OpenAI's 'reasoning' releases, the benefits of using GPT-4.5 are not immediately clear. Though, in the model's system card and in a previous interview with WIRED, the OpenAI researchers who worked on GPT-4.5 claimed improvements can be felt in the anthropomorphic aspects of the model, like a stronger intuition and a deeper understanding of emotion. After sitting in OpenAI's office last year and listening to leadership talk about the startup's plan to further productize ChatGPT as useful software, this was not the release I expected in 2025. Rather than take a more utilitarian approach, this model attempts to be more emotional....

Artificial intelligence (AI) systems with human-level reasoning are unlikely to be achieved through the approach and technology that have dominated the current boom in AI, according to a survey of hundreds of people working in the field. More than three-quarters of respondents said that enlarging current AI systems ' an approach that has been hugely successful in enhancing their performance over the past few years ' is unlikely to lead to what is known as artificial general intelligence (AGI). An even higher proportion said that neural networks, the fundamental technology behind generative AI, alone probably cannot match or surpass human intelligence. And the very pursuit of these capabilities also provokes scepticism: less than one-quarter of respondents said that achieving AGI should be the core mission of the AI research community. "I don't know if reaching human-level intelligence is the right goal,' says Francesca Rossi, an AI researcher at IBM in Yorktown Heights, New York, who spearheaded the survey in her role as president of the Association for the Advancement of Artificial Intelligence (AAAI) in Washington DC. 'AI should support human growth, learning and improvement, not replace us.'...

Google co-founder Sergey Brin sent a memo to employees this week urging them to return to the office 'at least every weekday' in order to help the company win the AGI race, The New York Times reports. Brin told employees that working 60 hours a week is a 'sweet spot' for productivity. While Brin's memo is not an official policy change for Google, which requires workers to come to work in person three days a week, it does show the pressure Silicon Valley giants are feeling to compete in AI. The memo also indicates that Brin believes Google could build AGI, a superintelligent AI system on par with human intelligence. Brin has reportedly returned to Google in recent years to help the company regain its footing in the AI race. Google was caught by surprise by OpenAI's 2022 release of ChatGPT, but has worked diligently to catch up with industry leading AI models of its own....

These days we are hearing more about Reinforcement Learning (RL) in the world of generative AI. To some extent, foundation models have served almost as a forcing function in the renaissance of RL which, as an AI method, experienced quite a bit of challenges over the last few years. RL has long been heralded as a general framework for achieving artificial intelligence, promising agents that learn optimal behavior through trial and error. In 2016, DeepMind's AlphaGo victory over a world champion in the complex board game Go stunned the world and raised expectations sky-high. AlphaGo's success suggested that deep RL techniques, combined with powerful neural networks, could crack problems once thought unattainable. Indeed, in the aftermath of this breakthrough, many viewed RL as a potential path to artificial general intelligence (AGI), fueling tremendous hype and investment Yet reality proved more sobering: after AlphaGo, RL's impact beyond controlled settings remained limited, and progress toward broader AI applications stalled....

Meta CEO Mark Zuckerberg has pledged to make artificial general intelligence (AGI) ' which is roughly defined as AI that can accomplish any task a human can ' openly available one day. But in a new policy document, Meta suggests that there are certain scenarios in which it may not release a highly capable AI system it developed internally. As Meta defines them, both 'high-risk' and 'critical-risk' systems are capable of aiding in cybersecurity, chemical, and biological attacks, the difference being that 'critical-risk' systems could result in a 'catastrophic outcome [that] cannot be mitigated in [a] proposed deployment context.' High-risk systems, by contrast, might make an attack easier to carry out but not as reliably or dependably as a critical risk system. Which sort of attacks are we talking about here' Meta gives a few examples, like the 'automated end-to-end compromise of a best-practice-protected corporate-scale environment' and the 'proliferation of high-impact biological weapons.' The list of possible catastrophes in Meta's document is far from exhaustive, the company acknowledges, but includes those that Meta believes to be 'the most urgent' and plausible to arise as a direct result of releasing a powerful AI system....

Senior Audrey Lorvo is researching AI safety, which seeks to ensure increasingly intelligent AI models are reliable and can benefit humanity. The growing field focuses on technical challenges like robustness and AI alignment with human values, as well as societal concerns like transparency and accountability. Practitioners are also concerned with the potential existential risks associated with increasingly powerful AI tools. 'Ensuring AI isn't misused or acts contrary to our intentions is increasingly important as we approach artificial general intelligence (AGI),' says Lorvo, a computer science, economics, and data science major. AGI describes the potential of artificial intelligence to match or surpass human cognitive capabilities. An MIT Schwarzman College of Computing Social and Ethical Responsibilities of Computing (SERC) scholar, Lorvo looks closely at how AI might automate AI research and development processes and practices. A member of the Big Data research group, she's investigating the social and economic implications associated with AI's potential to accelerate research on itself and how to effectively communicate these ideas and potential impacts to general audiences including legislators, strategic advisors, and others....