Models & Labs · Americas

Cohere offers to put agents in lockdown mode with strict ACLs

Credited to The Register · theregister.com · 2d ago

Photograph · The Register

While OpenAI and Anthropic stoke fears over rogue agents, Canadian model dev Cohere promises enterprises a safer and more consistent experience. On Monday, the company said it revamped its North agent harness, which launched early last year, to improve collaboration, access control, token spend, and overall security of the platform.

As you'd expect from an enterprise focused agent framework, Cohere's North 2 is designed to tie into existing knowledge bases and SaaS apps in order to automate various business processes.

North 2 introduces a variety of features and functions that should be familiar to anyone who's used Claude Code or OpenClaw. Among them is the concept of skills, libraries, and automations.

Skills are arguably the simplest, and are essentially standard operating procedures documenting how the agent harness should complete tasks. The skills are often generated by working with the agent to complete a task and then documenting which steps achieved the best results.

With North 2, Cohere says that it has made it easier for these skills to be shared so that users aren't wasting time reinventing the wheel. Presumably, this should improve consistency by avoiding having the agent take different routes to achieving its goal, something that might miss key information or nuance.

To facilitate the creation of new skills, North 2 also introduces the concept of automations, generic templates that can be customized using a drag-and-drop graphical interface, not unlike LangFlow, which we looked at earlier this year.

Alongside skills and automations, Cohere's North 2 does something similar for shared knowledge and assets, which it calls libraries, to ensure that agents are working off of the same datasets. Finally, North 2 adds memory, a core feature of most modern agent harnesses, to ensure that agents can maintain context across multiple sessions.

In some sense, these features are a bit like self-generating macros, but rather than being limited to Excel, they work across multiple applications and data sources.

Sovereign AI remains a major talking point for Cohere, which says enterprises can deploy North 2 where they like and use their preferred models. If enterprises want to deploy the harness on-prem in an air-gapped environment, they can. If they prefer to run it in the cloud, that's also an option.

Along with new features aimed at collaboration and automation, North 2 implements new guardrails designed to help enterprises get a handle on their token spend and access controls.

Flow control functionality, meanwhile, promises greater visibility into which departments are hogging all the tokens, while access control functionality offers admins the ability to assign access control lists to various libraries and skills so that interns can't get their hands on proprietary data just because they asked for it.

North 2 is only the latest in a slew of enterprise focused agentic AI platforms which have been rolled out over the last year. Essentially every major and minor cloud provider has introduced some kind of agent harness tailored to enterprise needs. The competition has only gotten hotter over the last few weeks as OpenAI, Meta and others have set their sights on the enterprise. ®

Chips & SupplyUnited States

Wall Street banks launch record $60bn chip deal for Broadcom and Anthropic

Credited to Financial Times$ · ft.com2d ago

Useful

Syndication of the massive financing package tests lending appetite amid growing concerns over mounting AI debt

View the article · $Financial Times

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Models & Labs · United States

Report: Amazon to offload $8B worth of AI chips, lease them back

Credited to SiliconANGLE · siliconangle.com · 5d ago

Photograph · SiliconANGLE

Amazon.com Inc. reportedly plans to offload some of its artificial intelligence chips and then lease them back.

The Financial Times today cited sources as saying that the transaction would involve a special purpose vehicle, or SPV. A SPV is a type of legal entity that enterprises set up to optimize the administrative aspects of large deals. Such vehicles often take the form of a standalone company without any employees.

Amazon’s plan would see it transfer about $8 billion worth of chips to the SPV. From there, the SPV will issue debt and a 10% equity stake to external investors. Amazon has reportedly been holding talks with potential backers for several weeks.

The chips at the center of the deal are reportedly Grace Blackwell accelerators. Each such device includes two of Nvidia Corp.’s Blackwell graphics processing unit and one Grace central processing unit. A custom interconnect, NVLink-C2C, links together the GPUs and CPU to facilitate data movement.

Blackwell was Nvidia’s flagship AI accelerator until last March. That month, it introduced an enhanced version called Blackwell Ultra that includes more memory. Nvidia’s current flagship GPU, the Rubin, is several times faster than both chips.

In August, Amazon agreed to buy 2 million additional GPUs from the chipmaker through 2028. The deal encompasses Blackwell Ultra, Rubin and an upcoming accelerator called Rubin Ultra that is set to launch next year.

Modal Inc., a venture-backed AI infrastructure provider, estimates that a Grace Blackwell accelerator costs between $60,000 to $70,000. Given the expected $8 billion price tag of Amazon’s SPV deal, that suggests the company intends to offload between 114,000 and 133,000 chips.

The accelerators are said to be installed in five Amazon data centers. Some of the accelerators are owned by the company, while others are leased. Amazon reportedly plans to continue using the chips after offloading them by signing a lease agreement.

Moving the chips to an SPV would remove them from Amazon’s balance sheet. Perhaps more importantly, it would also remove the debt that the SPV reportedly plans to raise.

Moving debt off a company’s balance sheet improves its debt-to-equity ratio, a metric that factors into its credit rating. A company’s credit rating, in turn, influences its ability to borrow funds and the cost of doing so.

The Wall Street Journal recently reported that Amazon, Google LLC and seven other tech giants together have $3 trillion in off-balance-sheet obligations. Much of that debt is tied to AI infrastructure projects. Meta Platforms Inc., for example, has sold a 80% stake in its flagship Hyperion data center campus to an investment firm.

Tech giants are also optimizing the financial structure of their AI deals in other ways. On Wednesday, the New York Times reported that Meta has claimed billions of dollars in innovation tax credits by characterizing its AI data centers as experimental projects.

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