Artificial intelligence

Artificial intelligence

OpenAI CEO Sam Altman is now maybe taking a page out of Elon Musk's and Trump's playbook, and posting a cheeky AI-generated photo of himself as a sexy calendar firefighter to Xitter. In what's apparently intended to show off the capabilities of Images 1.5, the new image-creation module in ChatGPT, OpenAI's Sam Altman posted the example below. The embedded version cuts off his head, but click through and you'll see it's Sam.

For many, enterprise AI adoption depends on the availability of high-quality open-weights models. Exposing sensitive customer data or hard-fought intellectual property to APIs so you can use closed models like ChatGPT is a non-starter. Outside of Chinese AI labs, the few open-weights models available today don't compare favorably to the proprietary models from the likes of OpenAI or Anthropic. This isn't just a problem for enterprise adoption; it's a roadblock to Nvidia's agentic AI vision that the GPU giant is keen to clear.

Last week at AWS re:Invent, amid many product announcements and cloud messages, AWS introduced AWS AI Factories. The press release emphasizes accelerating artificial intelligence development with Trainium, Nvidia GPUs, and reliable, secure infrastructure, all delivered with the ease, security, and sophistication you've come to expect from Amazon's cloud. If you're an enterprise leader with a budget and a mandate to "do more with AI," the announcement is likely to prompt C-suite inquiries about deploying your own factory.

Others foresee a revolution that might add between US$17 trillion and $26 trillion to annual global economic output and automate up to half of today's jobs by 2045. But even before the full impacts materialize, beliefs about our AI future affect the economy today - steering young people's career choices, guiding government policy and driving vast investment flows into semiconductors and other components of data centres.

Google's at it again, once more insisting that AI is something people need or want more of in their lives. The latest move comes from YouTube Gaming, which announced an open beta for a project called Playables Builder. This allows select YouTube Creators to use a "prototype web app built using Gemini 3" to make bite-sized games, no coding required.

Former Palantir CIO Jim Siders has departed the company to join Shield Technology Partners as CEO, in a bid he says is meant to bring AI to bear in the sprawling managed services landscape.

Rodney Brooks, the cofounder of Roomba vacuum creator iRobot, said the idea of humanoid robots as catchall assistants, the future Elon Musk envisions, is "pure fantasy thinking," in part because robots are coordination-challenged. "Today's humanoid robots will not learn how to be dexterous despite the hundreds of millions, or perhaps many billions of dollars, being donated by VCs and major tech companies to pay for their training," said Brooks in a blog post.

Lyft has rearchitected its machine learning platform LyftLearn into a hybrid system, moving offline workloads to AWS SageMaker while retaining Kubernetes for online model serving. Its decision to choose managed services where operational complexity was highest, while maintaining custom infrastructure where control mattered most, offers a pragmatic alternative to unified platform strategies. Lyft's engineers migrated LyftLearn Compute, which manages training and batch processing, to AWS SageMaker, eliminating background watcher services, cluster autoscaling challenges, and eventually-consistent state management, which had consumed significant engineering effort.

If trends continue, Google's ecosystem may evolve as follows: 1. Topic clusters go mainstream. To cut LLM-generated clutter, expensive features like topic clustering, once restricted to niche products like Google News (since the 2010s), will go mainstream across Search, Gemini, Discover, and YouTube. Discover's mid-2025 AI summary cards already signaled this shift. Here's how topic clusters look on YouTube. 2. On Discover, YouTube, and Gemini, traffic will go to fewer, deeper stories on a topic.

"As efforts shift from hype to execution, businesses are under pressure to show ROI from rising AI spend," the company wrote. "Large-cap CEOs are seeing solid returns on current programs, particularly across administration, internal efficiency, and customer-facing applications. However, 84% of these CEOs predict that positive returns from new AI initiatives will take longer than six months to achieve. In contrast, investors are pushing for faster impact: 53% expect positive ROI in six months or less."

Artificial intelligence has, to use another ubiquitous word, made cognition precariously abundant. Answers arrive instantly and patterns surface with little to no effort. Judgment is technologically packaged and delivered with a confidence that increasingly rivals, if not often exceeds our own. My central point here is that this isn't simply another technological advance but marks the first time human cognition itself appears to be on the obsolescence curve.

It wasn't like two months ago, but constant,

Slurm is used to schedule computing tasks and allocate resources within large server clusters in research, industry, and government. SchedMD was founded in 2010 by the original developers of Slurm. The company not only focuses on the further development of the software, but also provides commercial support and advice to organizations that use Slurm in production. According to SiliconANGLE, SchedMD serves several hundred customers, including government agencies, banks, and organizations in the healthcare sector.

Experts have been urgently warning that allowing young kids to play with AI-powered toys could have negative consequences, from stunting childhood development by blurring the boundary between imagination and reality to exposing tots to inappropriate subject matters and AI hallucinations. And as it quickly turned out, their worries were not unfounded. Toy makers have unleashed a flood of AI toys that have already been caught telling tykes how to find knives, light fires with matches, and giving crash courses in sexual fetishes.

Hugging Face has announced the first release candidate of Transformers v5. This marks an important step for the Transformers library, which has evolved significantly since the v4 release five years ago. It has transitioned from a specialized model toolkit to a key resource in AI development, currently recording over three million installations per day, with a total of more than 1.2 billion installs.

The result came as a surprise to researchers at the Icaro Lab in Italy. They set out to examine whether different language styles in this case prompts in the form of poems influence AI models' ability to recognize banned or harmful content. And the answer was a resounding yes. Using poetry, researchers were able to get around safety guardrails and it's not entirely clear why.

Matt Garman, the CEO of Amazon Web Services, is looking to change that. At the recent AWS re:Invent conference, Garman announced a bunch of frontier AI models, as well as a tool designed to let AWS customers build models of their own. That tool, Nova Forge, allows companies to engage in what's known as custom pretraining-adding their data in the process of building a base model-which should allow for vastly more customized models that suit a given company's needs.

Senior partners at the global management consulting firm, which has been steadily cutting its worldwide workforce over the past few years, are understood to have held initial talks with the heads of non-client-facing departments about shrinking their teams by as much as 10 per cent. A McKinsey spokesman would not confirm how many roles were at risk, but Bloomberg, which first reported the plans, estimated that there could be "a few thousand" layoffs staggered over the next 18 to 24 months.

SAN and NAS are distinct ways of deploying storage. They differ at fundamental levels of storage architecture, according to their relation to file system and block and physical addressing, but also the network or fabric by which input/output (I/O) travels. Here, we look at the key differences in performance and applicability between block and file storage, focusing on key contemporary workloads in artificial intelligence (AI), virtual machines and containerised environments.

I recently implemented a feature here on my own blog that uses OpenAI's GPT to help me correct spelling and punctuation in posted blog comments. Because I was curious, and because the scale is so small, I take the same prompt and fire it off three times. The pseudo code looks like this: for model in ("gpt-5", "gpt-5-mini", "gpt-5-nano"): response = completion( model=model, api_key=settings.OPENAI_API_KEY, messages=messages, ) record_response(response)

ChatGPT predicts Bitcoin closes the year around $86,000-down 3.9% from current levels-while top analysts target $111,000, creating a $25,000 gap that can't both be right. Bitcoin ( ) hit $126,000 in October 2025, then crashed back to the upper $80Ks by December. Now the question dividing markets: will Bitcoin ETF inflows of $223 million daily and surging institutional demand push prices to $111K, or will technical indicators and ChatGPT's bearish signals prove correct at $86K?