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But now, just 24 hours after shipping the open source Qwen3.5 small model series—a release that drew public praise from Elon Musk for its "impressive intelligence density"—the project’s technical architect and several other Qwen team members have exited the company under unclear circumstances, raising questions and concerns from around the world about the future direction of the Qwen team and its focus on open source. | |
The Algorithmic Bridge Substack - How Many People Does It Take to Kill a ChatGPT? | After OpenAI announced its Pentagon deal this past weekend, ChatGPT mobile app uninstalls in the US spiked 295%. Downloads dropped 13%. One-star reviews surged 775% in a single day; five-star reviews fell by half. The QuitGPT campaign—a grassroots initiative that started in January 2026—claims 2.5 million signatures. My entire X timeline is people urging others to cancel ChatGPT and switch to Claude. |
The Labs' new technique, Self-Flow, introduces an "information asymmetry" to solve this. Using a technique called Dual-Timestep Scheduling, the system applies different levels of noise to different parts of the input. The student receives a heavily corrupted version of the data, while the teacher—an Exponential Moving Average (EMA) version of the model itself—sees a "cleaner" version of the same data. | |
SiliconANGLE - Microsoft open-sources multimodal reasoning model with 15B parameters | Microsoft compared the algorithm to several similarly sized reasoning models using a set of open-source benchmarks. Phi-4-reasoning-vision-15B scored 17% higher than Google LLC’s gemma-3-12b-it on MathVista_Mini, a benchmark that comprises multimodal math questions. The model also achieved higher scores across more than a half-dozen other evaluations. |
The 15-billion-parameter model, available immediately through Microsoft Foundry, HuggingFace, and GitHub under a permissive license, processes both images and text and can reason through complex math and science problems, interpret charts and documents, navigate graphical user interfaces, and handle everyday visual tasks like captioning photos and reading receipts. | |
Educating AI Substack - When AI Says “This Quote Is Accurate,” You Shouldn’t Believe It | They do not retrieve text the way databases do. They reconstruct language probabilistically, token by token, based on patterns, likelihoods, and semantic approximation. Even when the original document is fully present in the prompt, the model does not perform exact character-by-character comparison. It generates what seems right. And what seems right is often close enough to feel authoritative without being literally accurate. |
ZDNet - Will AI make cybersecurity obsolete or is Silicon Valley confabulating again? | Wall Street observers think there is a real possibility that AI firms' tools will displace the traditional cybersecurity offerings from companies such as Palo Alto Networks, Zscaler, and Check Point Software. A related field, called observability, is also threatened, including firms such as Dynatrace that sell tools to detect system failures. |
A little over a year ago, China’s open source ‘DeepSeek’ up-ended the US AI developer community with its innovations. Now it seems that the now US OpenClaw, with its open source AI Agents running on local (mainly Apple computers), is up-ending the AI/tech developer community in China. Exponentially benefiting and expanding the AI ecosystems in both places. Let’s unpack. | |
It’s a startling mea culpa from Altman - “Good learning experience for me as we face higher-stakes decisions in the future” - and one triggered presumably by a combination of online opprobrium aimed at the company, an uptick in cancellations of ChatGPT, and the rise of Anthropic’s Claude app to the number one slot on the AppStore from being #131 a month earlier. | |
SiliconANGLE - Anthropic makes switching from competitors easier with new transfer memory tool | As Anthropic PBC’s Claude chatbot moves to the top of the app charts after a spat with the Trump administration, the company has introduced a memory import feature that will allow new customers to import their conversations from rival chatbots and start again with Claude. |
To put this into perspective, these models are on the order of the smallest general purpose models lately shipped by any lab around the world, comparable more to MIT offshoot LiquidAI's LFM2 series, which also have several hundred million or billion parameters, than the estimated trillion parameters (model settings) reportedly used for the flagship models from OpenAI, Anthropic, and Google's Gemini series. | |
Given that the Finance role is one of those frequently cited as vulnerable to being automated by AI, Intuit is clearly on the front line of those firms that find themselves caught in the fall-out from the so-called ‘SaaSpocalypse’. | |
The first time my team shipped an agent into a real SaaS workflow, the product demo looked perfect. The production bill did not. A small percentage of sessions hit messy edge cases, and our agent responded the way most agents do: it tried harder. It re-planned, re-queried, re-summarized and retried tool calls. Users saw a slightly slower response, and finance saw a step-change in variable spend. | |
Computerworld - Trump administration bans Anthropic, seemingly embraces OpenAI | Under the plan, according to Axios, the Defense Department would sever a contract, worth up to $200 million, with Anthropic, and require defense contractors and other vendors to certify they are not using Anthropic’s Claude model in work tied to the Pentagon. The administration is allowing a six-month window to give agencies and contractors time to transition to alternatives. |
SiliconANGLE - Satya’s sacrifice: Why agents threaten Office and how Microsoft responds | The real issue is that Nadella’s prediction exposes a vulnerability to Microsoft’s single-user productivity franchise. Specifically, we see agents and a new work surface as the primary interface for knowledge work. Office risks being partially disintermediated – reduced from the place where humans and agents collaborate to a set of file formats that agents can create, edit and orchestrate using open-source engines while users live inside a new work surface – some container that’s more editable than Claude Cowork, and where Word, Excel and PowerPoint are plug-ins |
Diginomica - A little bit of history repeating? Déjà vu lessons for AI code development | The code generation capabilities are intriguing and often capture a lot of software customer interest. The WOW factor on this gets people excited – really excited – but, maybe we should look to the past at previous WOW moments in IT and see if a more considered, premeditated approach to AI is appropriate. |
ZDNet - Is Perplexity's new Computer a safer version of OpenClaw? How it works | On Wednesday, the company introduced Computer, a multiagent orchestration system that harnesses the strongest capabilities from more than a dozen frontier AI models. Currently available only to Perplexity Max users -- and expected to roll out to Enterprise and Pro subscribers in the coming weeks -- "Computer is a general-purpose digital worker," the company wrote in a press release, that "reasons, delegates, searches, builds, remembers, codes, and delivers." |
Computerworld - LinkedIn moves to offer skill validations in the AI era | The Verified AI Skills program unveiled in January involves LinkedIn partnering with AI tool providers to automatically validate and display a user’s proficiency directly in their certification section. The initial partners include Lovable, Replit, Relay.app, and Descript, which will track AI proficiency of candidates using their tools to create AI apps. |
ZDNet - 90% of sales teams use AI agents - but half of them have the same data problem | AI agent adoption requires better data and fewer tools. Sales teams are unifying data and simplifying tech to improve AI and agent outcomes. Sales pros have data concerns, such as manual errors and duplicate data. Others say bloated tech stacks delay their AI initiatives. 84% of teams without an all-in-one platform plan to consolidate tech |
But what Claude did was a real eye-opener. He downloaded the service’s command-line interface and used it to do all the work (except logging in—I had to do that). He couldn’t (yet, I suppose) use the website itself. But a CLI? Child’s play. | |
The company is positioning Red Hat AI Enterprise as a “foundation for AI production” that provides capabilities including AI inference, model tuning, customization, deployment and management tools in a single package. It’s meant to support any kind of AI model in any environment, including the cloud or on-premises. | |
AI Workplace Wellness Substack - The Quiet Rise of AI Fatigue - by Paul Chaney | One of Khare’s most striking observations is how AI changes the nature of work itself. Instead of building things deeply, many engineers now spend their days reviewing AI outputs: editing, validating, correcting. He likened the experience to judging an endless assembly line of code. |
SiliconANGLE - Anthropic slams Chinese AI firms for harvesting data from its Claude chatbot | The process of using data from one AI system to train another is known as “distillation,” and it’s a fairly common technique for developers. But Anthropic’s terms of service prohibit anyone from harvesting Claude’s responses in this way. In addition, they’re meant to prevent its chatbot from being used by anyone in China. |
Marcus on AI Substack - Turns out Generative AI was a scam - by Gary Marcus | None of what Ovide had to say about the overestimation of Generative AI should actually come as a surprise. Generative AI has been inherently unreliable from the start; none of the problems that I warned about over the last half decade has been properly solved. Large language models still hallucinate, and they still make boneheaded errors; they still lack a proper concept of reality. They often produce workslop. A recent survey called The Remote Labor Index found that they could only do 2.5% of human tasks, and that is a massive overestimate, since literally everything that requires physical labor was excluded. |
SiliconANGLE - Why real-time voice AI is harder than it sounds | But even strong models are only part of the equation. Enterprise voice systems must be deployed like infrastructure, and the needs of business buyers are fundamentally different from those of consumers. “It has to have low latency, it has to have high throughput, it has to be reliable, it has to be debunkable, it has to be adaptable and get better over time,” Stephenson said. |
He added, “Enforcement is the hard part. There’s no magic scanner that can reliably detect AI‑generated code and there may never be such a scanner. The only workable model is cultural: require contributors to explain their code, justify their choices, and demonstrate they understand what they’re submitting. You can’t always detect AI, but you can absolutely detect when someone doesn’t know what they shipped.” | |
Despite the promise of smaller models, many of the tools on display in the exposition hall at Developer Week were designed to facilitate access to leading AI models such as those from OpenAI Group PBC, Anthropic PBC and China’s DeepSeek. The developer community is looking closely at the merits of both small and large models, a situation that will likely become clearer over the coming year. | |
ZDNet - Is an AI subscription worth it? How to choose your premium chatbot plan - and what not to do | All have surprisingly capable free plans. ChatGPT, Gemini, and Grok have $8-per-month basic plans that provide a bit more interaction capability but use lesser-capability AI engines. All but Grok offer $20-per-month standard plans. These are the sweet spot for price and performance. Grok's equivalent, called SuperGrok, is $30 per month instead of $20. |
Normally, when big-name talent leaves Silicon Valley giants, the PR language is vanilla: they’re headed for a “new chapter” or “grateful for the journey” — or maybe there’s some vague hints about a stealth startup. In the world of AI, though, recent exits read more like whistleblower warnings |