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Bank of America spent millions on anti-money-laundering tech, but not enough to avoid a $1.2B fine15:21 Bank of America has had to spend big on IT in response to an AI security audit and findings that its anti-money-laundering (AML) controls were lacking. The bank was fined a whopping $1.2 billion for money laundering offences this week, after banking authorities identified a lax attitude to compliance. “We understand the seriousness of compliance, and we are responsible for getting it right,” Bank… The $690 billion cloud spending spree11:47 Every quarter, I look at the capital expenditure numbers coming out of the major cloud providers, and every quarter, they manage to surprise me. This time, though, we’ve crossed into territory that’s genuinely hard to process. The five biggest US cloud and AI infrastructure providers (Microsoft, Alphabet, Amazon, Meta, and Oracle) have collectively committed to spending between $660 billion and $… Pop the champagne, Python 3.15 is here!11:47 The best Python yet isn’t just faster than before. It’s also smarter at telling you what’s wrong, better at letting you profile applications, and loaded with new language features to give you a better programming experience. Top picks for Python readers on InfoWorld The best new features in Python 3.15 Python 3.15 is now GA, and it’s the best Python yet. Get your hands on its improved JIT compila… Cyberattack AIs must be trained only on air-gapped systems, hundreds of AI researchers say10:54 Current security procedures for training AI models are inadequate, hundreds of AI researchers have warned governments and the AI community. They are calling for tougher rules and the establishment of a new international body overseeing best practice for AI development. In an open letter the AI specialists — 487, at time of publication, including many senior academics — called for more AI safety r… TypeSafe’s Jev ‘even more susceptible to attack’ than LLMs, says security vendor2:55 Although the Jev model rolled out last month by TypeSafe claims to have significant advantages over traditional LLMs, a security report published Wednesday argued that its streamlined approach makes it more vulnerable to some kinds of attack, compared to traditional LLMs. “In some cases, [Jev] is even more vulnerable to attacks, with both adversarial text attacks and prompt injection being able t… ServiceNow makes it easier to build AI agents, gives them verifiable identities15.října ServiceNow is giving its AI Control Tower new features to make AI agents more governable — and a new name, Super Intelligence Control Tower (SICT), to please the US President. It is also updating EmployeeWorks to make building AI agents easier. AI Passport, a new component of SICT, gives every agent, whether from ServiceNow or a third party, a verifiable identity, and provides runtime control ove… Google aims to make BigQuery spending on AI functions more predictable with token quotas15.října Google has made daily token quotas generally available for BigQuery’s generative AI functions to give enterprises a way to limit AI consumption by project and individual user. These quotas, which can be managed via the IAM and Admin tab in the Google Cloud Console, cover both input and output tokens at the project and individual-user levels per day and apply to the AI.GENERATE, AI.GENERATE_TABLE,… Your AI agent needs more than memory. It needs reliable state15.října Most teams building AI agents are pouring effort into better memory, longer context windows, conversation summaries, retrieval systems that pull up anything the agent has ever seen. These are useful tools. But they do not solve the problem of knowing whether an action actually completed. Memory tells an agent what happened. It doesn’t tell the agent what’s true right now. And for any agent that t… Building Fabric Apps with Microsoft’s Rayfin15.října Using vibe coding to scratch an itch has many of the same issues as using low-code and no-code development tools. That’s not surprising. Putting together something quickly to solve a specific problem lacks the level of discipline of software engineering, introducing inefficiencies that come from not following architectural guidelines and policies. I recently reviewed the AI-generated code I used … When an agent acts, who is accountable?15.října For most of the history of enterprise software, accountability has been relatively easy to understand. A person logs in, a person has a set of permissions, and a person takes an action. If something goes wrong, you can usually work backwards from there. Agentic AI changes that. We are moving from systems that suggest what someone should do to systems that can actually do it. Agents can access too… Google positions Gemini 4 Argon for long-horizon agentic work14.října Google has launched Gemini 4 Argon, a new flagship AI model aimed at complex enterprise and software-development workloads, pairing claims of stronger coding performance and advanced reasoning with an introductory pricing model that doubles after November 30. The model “excels at deep work in complex, real-world tasks,” Koray Kavukcuoglu, senior vice president of Google DeepMind and chief AI arch… 5 agentic AI trade-offs to consider before production14.října Companies across industries are moving quickly to build agentic AI systems. But getting an agent to work in a prototype is very different from getting one to perform reliably in production. Once agentic AI systems encounter real-world requirements around speed, accuracy and cost – the trade-offs become much harder to ignore. Across the many agentic AI projects I have worked on, one expectation co… It’s time to rewrite all that old code14.října The first substantial software project I ever undertook (at least it seemed substantial at the time) was porting the famous text-based Star Trek game from an old newspaper I found to an IBM 5100 “luggable” computer in the mid-1970s. My father, who was a cardiologist, was an early advocate for computing in medicine, and he used an IBM 5100 at work. He would bring this beast home on the weekends an… Seven ways to encourage critical thinking in AI users14.října Employees are increasingly using large language models (LLMs) and AI agents to get work done. Many are using agents to complete tasks, and others are using LLMs to generate content, vibe coding tools to develop applications, and agent orchestration platforms to automate workflows. According to Kyndryl’s People Readiness Report , while 57% of organizations have embedded AI into core processes or d… What building an Android weather app taught me about designing for reliability14.října I spent 13 years building Android apps, and for most of them, the backend was someone else’s problem. Building Weather Pal, my own forecast app, broke that habit fast. It taught me that mobile reliability is rarely about whether your server responded. It is about what happens to your data between fetch and display, and about who else is drinking from the pipe you pay for. Two incidents made that … |