Today: Anthropic discloses how Chinese hackers used its Claude AI model to launch several cyberattacks, Cursor hits a big milestone, and the latest enterprise moves.
Today: An update on our independent journalism mission and a pitch to our loyal readers, CoreWeave's strong third-quarter earnings masked a fourth-quarter supply problem, and the latest funding rounds in enterprise tech.
Today on Product Saturday: rivals Databricks and Snowflake roll out new tools that promise to help companies get their agents over the finish line and into production, and the quote of the week.
OpenAI and Anthropic both acknowledge they have a lot of work to do to improve the reliability of their services if they want to serve enterprise customers. But app developers also need to design their AI services with reliability in mind, which is hard when everyone is moving so fast.
When the CNCF accepts open-source projects, it requires that any trademarks related to the project be handed over. Synadia never did that, and is now backing down from an attempt to use its ownership of the trademark as leverage to regain control of NATS.
Model Context Protocol (MCP) was introduced last November by Anthropic, which called it "an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools." After kicking the tires for a few months, vendors are jumping on board.
It was only in the last six months that Canva decided generative AI coding assistants were good enough for its employees. It got there through a period of trial and error that suggests GenAI vendors need more flexible pricing strategies.
Vercel's serverless infrastructure was designed at a time when speed was the most important goal. AI apps are a little different, and Fluid Compute is an effort to rebuild that infrastructure for the AI era.
Even companies eager to jump on the GenAI bandwagon have struggled to organize their data and get past deployment hurdles, and nobody likes to spend all that time, effort, and money to build technology that can't be shipped because it can't be trusted.
AWS didn't ignore AI during Garman's presentation Tuesday, but it spent a significant amount of time on the services that turned it into a $100-billion a year enterprise computing powerhouse: compute, storage, and databases.
Despite recent challenges to their hegemony, x86 chips still power the vast majority of cloud and on-premises servers in use today. However, over all those years Intel and AMD tweaked x86 in subtle but incompatible ways to suit their own needs, and Tuesday's agreement is a promise to unify x86.
This week a U.K. regulatory agency published summaries of hearings it conducted this past July with AWS, Microsoft, and Google Their responses provide an interesting look into how the cloud providers see themselves, their competitors, and the current state of the market.
For years, Oracle tried to convince longtime database customers who wanted to shed their on-premises data centers to run those databases on Oracle's public infrastructure cloud, slamming AWS at every turn. Times have changed.
A generation of cloud architects, developers, and systems engineers has stayed loyal to AWS over nearly two decades in part because of its reputation for supporting anything it launched that was used by a customer to build their infrastructure. That commitment appears to be changing.
Kubernetes has become the second-most widely used open-source project in the world, behind only Linux itself, thanks to a dedicated community that celebrated its 10th birthday last week.
