AI-generated
Saturday, 26 September 2026 | 47 articles
Microsoft overhauled Copilot into a super app with Home, Code and Autopilot modes while Meta launched Muse for personal finance and Cisco reported over half of firms already run agentic AI in live network operations. Meanwhile, European tech leaders and the UN chief called for caution, warning against a reckless race to deploy AI without adequate safety measures.
Researchers introduced TimeBraid, a family of models that align pretrained language models with pretrained time-series foundation models. The goal is to combine strengths of both approaches for better understanding and forecasting of temporal data. Source: alphaxiv.org
Federal agencies don't always need the largest available AI model — picking a size that matches the actual task can lower costs and improve oversight. Experts argue this approach offers a more practical path to responsible AI adoption in government. Source: fedtechmagazine.com
Traditional herbal medicine has built up a vast but scattered body of knowledge about which plants may treat which illnesses. Language models are now being applied to sift through this sparse, fragmented historical data and reveal previously hidden herb-disease connections. Source: bioengineer.org
Anthropic announced that its Claude model helped identify a gene-editing system resembling CRISPR. Commentators caution this is unlikely to be a revolutionary scientific leap, more likely just another useful addition to the gene-editing toolbox. Source: newscientist.com
LLMs are increasingly used to offer text-based recommendations in fields like urban planning, design and public health. The growing role raises questions about whether these models can be trusted to provide sound ethical guidance in areas affecting people's wellbeing. Source: techxplore.com
Muse is Meta's new personal AI assistant designed to help users handle everyday financial tasks. Here's a look at how it works and what it can do for personal budgeting. Source: finance.yahoo.com
CLM-8B, developed by Stanford and Nvidia, stores reusable agent actions instead of recomputing them, achieving up to 9x faster performance than Jev in benchmark tests. The model targets AI agents that repeatedly use LLMs to select tools or rank outputs. Source: venturebeat.com
One user's AI agent saved $550 by booking restaurant reservations and flagged a phishing attempt, though it also burned $64 on a bad decision and raises real security concerns. Source: wired.com
A new Cisco survey shows 51% of organizations are using agentic AI in production network operations. The report examines what this means for MSPs handling network visibility, agent oversight, and control. Source: channelinsider.com
Gen's new data shows nearly one-third of people already use AI apps and agents, prompting the company to expand its Agent Trust Hub with a new AI Data Checker tool. The initiative aims to help users understand what happens to their data when interacting with AI systems. Source: tradingview.com
After decades of building direct relationships with shoppers, brands now face a shift as consumers increasingly rely on AI tools to discover and choose products. This raises concerns about losing control over the customer relationship to AI platforms. Source: customerexperiencedive.com
A new guide shows how to build an agentic platform for generating and reviewing contracts using Oracle Kubernetes Engine or OCI Enterprise AI. The setup relies on a microservices architecture combining LangGraph, OCI Queue, MCP, and an agent registry. Source: blogs.oracle.com
A group of European tech industry figures has joined growing warnings that AI could pose an existential risk, adding weight to calls for a slower pace of development. They say the industry itself recognizes the dangers and is genuinely worried about where things are heading. Source: fortune.com
The United Nations Secretary-General called on countries competing in AI development to cooperate rather than compromise safety standards. He stressed that the world cannot afford nations cutting corners on AI safety just to stay ahead in the race. Source: jamaica-gleaner.com
The piece uses the classic technology hype-cycle model, which describes adoption of new innovations in an S-curve from launch to mainstream use, to frame the debate over AI safety. It questions at what point AI development can be considered sufficiently safe for widespread trust. Source: cato.org
British AI researcher Jacob Coxon stirred controversy after resigning from Anthropic, publicly claiming AI poses serious risks. The commentary argues his warnings should be taken seriously rather than dismissed as speculative fiction. Source: orlandosentinel.com
A commentary piece reflects on recent unsettling statements about AI safety, citing Evan Hubinger, a safety researcher at Anthropic, the company behind Claude. The author argues it is still too early to know whether AI will ultimately prove harmful to humanity. Source: tennessean.com
New alarm bells raised from within the AI industry itself have revived a long-running discussion about the technology's potential dangers to humanity. The report notes this marks yet another round in a debate that has resurfaced repeatedly over the years. Source: vernonreporter.com
Microsoft's updated Copilot app now combines AI-assisted coding, always-on agents, and full versions of Word, Excel and PowerPoint. The launch marks an effort to boost adoption as competition with OpenAI and Anthropic intensifies. Source: geekwire.com
Microsoft is expanding Copilot's role as a workplace hub, unveiling a redesign that merges Office tools with an always-running Autopilot agent. The update also lets users host applications generated by AI directly within Copilot. Source: venturebeat.com
Microsoft unveiled a major Copilot update featuring a built-in coding assistant and an always-on AI agent called Autopilot. The update reflects the company's push to stay competitive in the fast-moving AI assistant market. Source: reuters.com
Microsoft is positioning its revamped Copilot as a central hub where users can chat with AI agents, generate code, and rely on a new Autopilot feature for automated tasks. The move is aimed squarely at business customers. Source: fortune.com
Microsoft is overhauling Copilot to better fit evolving work patterns, aiming to expand what individuals and organizations can achieve within a single AI assistant. The redesign bundles chat, coding tools, and workflow automation into one experience. Source: blogs.microsoft.com
Microsoft has relaunched Copilot with a shift in focus from personal use toward workplace productivity. Yahoo Finance's Dan Howley breaks down what has changed in the new version. Source: finance.yahoo.com
As Microsoft continues refining its AI strategy, the company has updated its Copilot app to consolidate multiple capabilities in one place. The move is seen as a direct response to growing competition from Anthropic. Source: cnbc.com
Microsoft is expanding Copilot's capabilities in an effort to win a larger share of the enterprise AI market, as rivals like OpenAI and Anthropic gain ground. A Gartner analyst noted the move reflects growing pressure in the competitive landscape. Source: ciodive.com
Microsoft is merging the consumer and enterprise versions of Copilot into a single product aimed primarily at corporate customers. The move effectively cedes ground in the crowded personal AI chatbot market to rivals. Source: bloomberg.com
Microsoft announced an updated Copilot app on Friday, marking another step in its effort to generate revenue from AI. The move is aimed at strengthening its position against other AI labs. Source: barrons.com
Researchers at Tarbiat Modares University in Tehran have developed a new architecture called DuoDiT that significantly cuts the cost of fine-tuning large image-generation models. The approach reportedly requires training just 2.6% of a model's total weights while still achieving strong results. Source: bioengineer.org
Singapore-based PixVerse has launched an AI-powered video generation tool aimed at helping creators and production teams turn text into finished video content. The feature is designed to streamline creative workflows for both individual creators and larger teams. Source: kitsapsun.com
Rosely AI has introduced a new Reels-focused capability on its AI social media platform, enabling short-form content built around AI-generated characters. The update expands the platform's growing ecosystem of AI-driven social features. Source: financialcontent.com
The article compares six leading AI tools that convert photos into videos, evaluating them by free tier limits, watermarks, commercial usage rights, and overall features. It aims to help readers pick the best option for their needs. Source: autogpt.net
The search term "AI image to video" has surged in popularity within the creative tech space this year. The article explores the reasons behind the rapid rise of these free tools across social platforms. Source: azbigmedia.com
Feather Robotics raised $7.6 million in pre-seed funding to grow its modular humanoid robot platform, aimed at letting third-party developers build physical AI applications on top of it. Source: theaiinsider.tech
MBody AI CEO John Fowler argues the robotics industry is repeating the hardware-fragmentation problem once seen between PC makers like Dell and HP, as companies deploy robots from multiple incompatible manufacturers. Source: benzinga.com
Startup Feather has launched a humanoid robot priced at $29,990, joining a wave of affordable machines that go beyond dancing demos and offer real functionality without the usual six-figure price tag. Source: forbes.com
Tesla's shift from EVs to humanoid robots is running into trouble, with complicated robotic hands and unhappy workers who are reluctant to help train their potential replacements. Source: arstechnica.com
Researchers have built a machine learning model that predicts how a patient's eyesight will develop after surgery for advanced diabetic retinopathy. The tool aims to help doctors anticipate long-term outcomes for one of diabetes' most feared complications. Source: bioengineer.org
Google details Project Suncatcher, its ambitious effort to explore putting AI computing hardware in space. The project covers testing how hardware endures space conditions and designing cooling systems for AI chips operating in orbit. Source: blog.google
Researchers at the University of Tartu combined machine learning with lab experiments to discover a new phthalazine-based drug candidate targeting deadly brain tumors. The approach pairs computational screening with rigorous validation to speed up drug discovery. Source: bioengineer.org
CTC is partnering with the U.S. Military Academy to advance research into AI security. The collaboration has produced a machine learning tool designed to guard defense systems against adversarial attacks and privacy vulnerabilities. Source: pabusinesscentral.com
Scientists have developed a machine learning approach to spot chemical compounds capable of safely steering honey bees away from crops treated with pesticides. The method could support efforts to safeguard these crucial pollinators. Source: growingproduce.com
A curated roundup tracks the biggest startup funding deals of 2026, focusing on $100 million-plus venture rounds raised by U.S.-based companies. Source: news.crunchbase.com
Island, which builds an enterprise-focused agentic control plane, closed a $400 million Series F round that more than doubled its valuation to $6.4 billion. Source: fintech.global
Nscale raised $3.36 billion in convertible notes led by Third Point, with NVIDIA, Apollo and Citadel among the backers. The company's total contracted value now exceeds $103 billion. Source: en.wowtale.net
Both Chinese tech giants announced updates on their semiconductor and AI infrastructure efforts, spanning custom AI chips, computing clusters, and new models. The news signals continued momentum in China's push for AI hardware independence. Source: hpcwire.com
Nvidia CEO Jensen Huang made another bold prediction on September 17, 2026, this time at an AI summit hosted by King Charles III. His commitment to double chip production reportedly commits over a third of the world's high-bandwidth memory supply. Source: shattered.io
AIskimIQ is an independent project. If you find it useful, you can support its development with a coffee.
Published by Martin Ševčík
26 September 2026 at 05:06
Fifty-one percent of organizations are now running agentic AI in live network operations, according to Cisco's latest survey — and I keep coming back to that number because it means agentic AI has quietly crossed from experiment to infrastructure. This isn't a chatbot answering customer questions anymore. This is software making decisions about how traffic flows through a company's network, in production, right now. The conversation about AI agents has shifted from "could this work" to "how do we keep it under control," and today's news makes that shift impossible to ignore.
Take the account of an AI agent that saved someone $550 booking restaurant reservations and caught a phishing attempt before it did damage. Genuinely useful. The same agent also burned $64 on a bad decision it made autonomously. That's the trade-off nobody wants to say out loud: these systems are good enough to trust with real money and real security decisions, but not yet reliable enough to trust unsupervised. Multiply that $64 mistake across an enterprise network with Cisco's half of surveyed companies running agents in NetOps, and you start to understand why oversight tooling for MSPs is becoming its own category rather than an afterthought. The economics only work if someone is watching the agent watch the network.
Meta's launch of Muse, a personal finance agent, pushes this same tension into consumer territory. Handing an AI agent visibility into your spending and budgeting is a different kind of trust exercise than letting one rebook a flight. Microsoft, meanwhile, is going the opposite direction with its Copilot relaunch — Home, Code, and Autopilot modes bundled into one assistant, explicitly designed to blur the line between chatting with AI and letting it act on your behalf inside your workflow. By the way, Stanford and Nvidia's CLM-8B is a quiet but important piece of infrastructure for exactly this future: it caches reusable agent actions instead of recomputing them every time, delivering up to 9x speedups. Efficiency work like this rarely makes headlines, but it's what makes it economically viable to run agents at the scale Cisco's survey describes.
Against all this momentum, it's worth sitting with the fact that a group of European tech leaders is now openly backing calls to slow AI development down, and the UN Secretary-General is warning against a "race to the bottom" on safety standards. I don't think these warnings are contradictory to the deployment numbers — I think they're a direct response to them. When half of companies are already running agentic systems in production and the industry's own senior figures say they're worried, that's not hypothetical risk anymore. It's happening at the same speed as the adoption. The question I keep asking is whether oversight infrastructure — the caching layers, the MSP monitoring tools, the guardrails — can mature as fast as the agents themselves are being deployed, or whether we're building the parachute after we've already jumped.