Connexion
OpenAI and Anthropic both recently released new models aimed at lowering costs. Anthropic announced Opus 5.5, the latest version of its main mass-market workhorse model, used for tasks like coding and other complex knowledge work.
And OpenAI announced GPT-6 Sol and Luna, the latest versions of its middle-of-the-road or smaller models focused on efficiency and speed.
Nvidia is reportedly moving forward to acquire Hugging Face for $12.9 billion. The acquisition could help the hardware giant expand and fortify its deep integration with the wider AI industry.
Among other things, Hugging Face is a cloud repository for AI models, similar in some respects to what GitHub is for conventional computer software. Developers and researchers search for models that meet certain criteria, download and run them, and fine-tune them into different variants that then get uploaded back up to Hugging Face.
IBM has rolled out the newest models in its family of open-weight large language models designed to be downloaded and self-hosted. The newly launched Granite 4.2 comes in 3B, 8B, and 30B parameter variants.
Like previous versions, IBM is taking a decoder-only approach here. These new releases offer a 128,000-token context window natively. The 8B and 30B variants (not the 3B one) also go through an agentic reinforcement-learning block; they were trained for expanded capabilities like using the terminal, searching the web, or using external tools. The 3B model supports tools too, but without the same level of specialized training.
For the past year or so, booksellers have suspected that AI firms are buying up huge lots of rare books, then destroying them after scanning them to train AI. But this was hard to prove until now, as 404 Media reports that an Airtag hidden in a rare book shows that at least one tech giant, in the race to advance its frontier models, is behind some of the bulk orders: Amazon.
On Monday, 404 Media revealed that it had connected with a bookseller who agreed to plant an Airtag in a rare book that was part of a bulk order. That Airtag was then tracked to an Amazon AI training facility in Las Vegas that housed a team focused on tearing books from their spines and scanning pages, 404 Media reported. Apparently tone-deaf to the escalating backlash over destructive book scanning, a logo on the door of that team’s warehouse, VGT3, showed a Tyrannosaurus rex preparing to devour a book, 404 Media documented.
Amazon declined to comment on 404 Media’s findings, only providing Ars with the same statement it gave to 404 Media, which does not mention AI training specifically.
Anthropic has accused the Chinese firm Alibaba of launching the largest attack yet attempting to clone Claude, as China races to match the capabilities of Anthropic's leading model following Mythos' release and subsequent restriction from foreign markets.
Ars obtained a June 10 letter sent to Senators Tim Scott (R-SC) and Elizabeth Warren (D-Mass.) one day ahead of a Senate committee hearing on “AI and the American Dream.” In the letter, Anthropic shared “new, confidential evidence of the largest campaign to illicitly extract Claude’s capabilities we have ever measured.”
The attacks occurred between April 22 and June 5, when “operators affiliated with Alibaba and Alibaba Qwen, Alibaba’s AI lab” allegedly generated “more than 28.8 million exchanges with Claude through almost 25,000 fraudulent accounts,” Anthropic said. Violating Claude's terms of service and access restrictions, this campaign “targeted some of Claude’s most valuable capabilities, such as agentic reasoning, software engineering, and long-horizon tasks.”
SAN FRANCISCO—At its Code with Claude developers' conference, Anthropic has introduced what it calls "dreaming" to Claude Managed Agents. Dreaming, in this case, is a process of going over recent events and identifying specific things that are worth storing in "memory" to inform future tasks and interactions.
Dreaming is a feature that is currently in research preview and limited to Managed Agents on the Claude Platform. Managed Agents are a higher-level alternative to building directly on the Messages API that Anthropic describes as a "pre-built, configurable agent harness that runs in managed infrastructure." It's intended for situations where you want multiple agents working on a task or project to some end point over several minutes or hours.
Anthropic describes dreaming as a scheduled process, in which sessions and memory stores are reviewed, and specific memories are curated. This is important because context windows are limited for LLMs, and important information can be lost over lengthy projects. On the chat side of things, many models use a process called compaction, whereby lengthy conversations are periodically analyzed, and the models attempt to remove irrelevant information from the context window while keeping what's actually important for the ongoing conversation, project, or task.
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