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OpenAI: GPT 5.6 Sol price reduction (until at least Nov 21)
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ESPN streaming plans are getting more expensive
ESPN is hiking the price of its subscription on September 17th, a change that will also impact its bundles with Disney Plus. In a support page spotted earlier by Sports Media Watch, ESPN says its ad-supported Select membership will cost $13.99 instead of $12.99 / month, while its Unlimited plan will rise to $31.99 from $29.99 / month. The annual ESPN Select plan is also going to $139.99 from $129.99 / year, and the annual Unlimited tier is increasing to $319.99 from $299.99 / year. Meanwhile, Disney Plus bundles with ESPN Select are going up in price as well. Here's a rundown of the changes: Disney Plus (with ads), Hulu (with ads), and ES … Read the full story at The Verge.
OpenAI is building AI agents for everything. Will everyone use them?
Inside the frontier lab’s push to bring AI agents from software engineers to the masses.
US nutrition startup Berry Street merges with India’s Healthify as GLP-1 trends upwards
Berry Street founder Noah Kotlove and Healthify founder Tushar Vashisht will act as co-CEOs of the new entity.
Anthropic’s new Claude Tag update lets its Slack agent read the full conversation — and jump in unprompted
Anthropic is making a calculated bet that the biggest bottleneck in enterprise AI isn t model intelligence — it s the fact that most people still use AI alone.In an exclusive interview with VentureBeat, Scott White, Anthropic s head of product for enterprise, laid out the company s thesis for what it calls multiplayer AI : a shift away from the single-user chatbot paradigm toward AI agents that operate across teams, read organizational context, and proactively insert themselves into work — sometimes without being asked.The strategy crystallized earlier this month when Anthropic updated Claude Tag, its agent that lives inside Slack channels, to read context across entire conversations rather than evaluating messages one at a time. According to the company, the change makes Claude roughly 30% better at deciding when — and, critically, when not — to jump into a conversation unprompted.That may sound like an incremental product update. White argues it represents something more fundamental:
De-Googled GrapheneOS is coming to Motorola’s foldables next year
The Razr Ultra line is among those due to receive GrapheneOS support next year. | Photo: Allison Johnson / The Verge GrapheneOS, an open source version of Android that prioritizes security and privacy, has detailed its plans for supporting Motorola smartphones. Official support is set to arrive next year, starting with traditional flagships, before rolling out to Motorola's foldable phones and perhaps cheaper models, eventually. In a Mastodon thread, the GrapheneOS Foundation announced that it will initially support a Motorola slab flagship phone, but will later support both Razr Fold and Razr Ultra foldables - the latter of which would be the first flip phone to officially run GrapheneOS. Graphene has always had stringent security standards when it com … Read the full story at The Verge.
IBM’s next-gen mainframe chip is the first to run Arm and Z workloads on the same cores
IBM is announcing today at the annual Hot Chips conference what may be the most consequential change to mainframe architecture in decades: a processor whose cores can natively execute both IBM s own instruction set and Arm s — switching between the two in nanoseconds.The chip, which will power the next generation of IBM Z and LinuxONE systems, is the first dual-architecture mainframe processor ever built. It is designed to let enterprises run the vast and fast-growing ecosystem of Arm-native Linux software — including the AI frameworks that increasingly define modern infrastructure — directly alongside the z/OS transaction-processing workloads that anchor the world s banks, insurers, and governments. As technology enthusiasts on both sides, we re really excited about being what I would consider one of the most powerful commercially available processors that ll be dual architecture, Tina Tarquinio, chief product officer for IBM Z and LinuxONE, told VentureBeat in an exclusive interview
We never use AI. For anything
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Humanoid robots smash Usain Bolt’s 100-meter record
Tiangong Ultra (left) also broke the 400 meter world record during this year’s World Humanoid Robot Games. | Image: Lintao Zhang/Getty Images The 9.58-second 100-meter dash record set by Usain Bolt in 2009 has been outpaced by Chinese robots participating at the World Humanoid Robot Games in Beijing. In a preliminary heat on Saturday, Tiangong Ultra, made by the Beijing Humanoid Robot Innovation Center, ran the distance in 9.39 seconds, followed by the Honor-developed Lightning at 9.47 seconds. It's one of several notable achievements to take place at the event, which can best be described as a sort of annual robot olympics that's designed to showcase advancements in bipedal bot technology. After launching in 2025, 2,056 robots from 16 countries are participating in this year's … Read the full story at The Verge.
Anthropic Claude and API service outages
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FDA clears blood test to aid evaluation for Alzheimer's disease
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Enterprise AI agents are only as reliable as the messiest documents behind them
Enterprise AI has largely been built around context engineering. Teams connect enterprise systems, generate chunks and embeddings, build retrieval pipelines, and assemble the context needed by individual AI applications. While this approach works well for isolated assistants and copilots, it treats enterprise knowledge as application-specific context rather than a shared enterprise asset.As organizations deploy more AI applications and agents, this model begins to break down. Different teams process the same documents, maintain separate embeddings and indexes, and create inconsistent representations of the same business knowledge. The challenge is no longer simply providing context to AI systems — it is managing enterprise knowledge itself.Why building context is not enough for enterprise AIThe common approach to enterprise AI today is to build context for individual applications. Teams connect enterprise systems, process the required information, generate retrieval representations suc