We’ve lost an icon. Margaret Hamilton, a computer science pioneer best known for her work at MIT leading development of the flight software for the Apollo missions to the moon, has died at 90. Read about her legacy via MIT News: https://t.co/ODkbdIsoHw
After 15 years of incredibly hard work, we’re partnering with Uber in a transaction valuing Delivery Hero at €13bn! 🚀
Very proud of what the team has built, and excited for the future.
Mythos appears to be the first class of models trained at scale on Blackwells. Then will be Vera Rubins. Pre-training isn't saturated. RL works. And there is *so much* computing coming online soon.
Buckle your chin strips. It's going to be fucking wild.
Many of the coding wrapper companies have recently changed their monetization to move almost exclusively to usage based.
It’s a necessary step for these companies to be GM+ but it will also accelerate the economic incentive for the underlying Foundational Models to “move up the stack” as well. Otherwise, the FMs risk being disintermediated by agents/tool calls.
Based on the recent valuations of the FMs, it’s unlikely that they can afford to let this happen.
Next few quarters will be really interesting.
@martin_casado@levie Fully agree. Yet the early agent frameworks seem to be overloaded with complexity and the experience suffers from too many inefficient handovers.
💡 Real-time AI agents are only as intelligent as the data they process. I joined the "Life Is But A Stream" podcast with Joseph Morais (@thedatagiant) to talk about how real-time data streaming powers agentic AI and intelligent copilots.
📺YouTube: https://t.co/jNkIDOrGF1
🎧Apple: https://t.co/v7faXmrfbL
🎙️Spotify: https://t.co/Y4oaPsjahj
💡 Real-time AI agents are no longer just an idea...they’re here.
Tune into the latest Life Is But A Stream episode with Joseph Morais (@thedatagiant) and Airy's Steffen Hoellinger as they dive into how real-time data streaming powers agentic AI and intelligent copilots.
📺 Watch it on YouTube: https://t.co/XhJayIr1Aa
🎧Listen Here: https://t.co/ixwB9zhyE2
Summary of my recent #FlinkForward talk "Building #Copilots with #FlinkSQL, LLMs & Vector DBs":
🤖 AI Assistants & self-serve AI/BI for streaming & batch data
🧠 AI-powered schema intelligence
🔄 Natural Language to generate Flink SQL jobs
⚙️ Continuous monitoring for agentic AI
𝐄𝐯𝐞𝐫𝐲 𝐒𝐲𝐬𝐭𝐞𝐦 𝐢𝐬 𝐚 𝐋𝐨𝐠
An idea on how to drastically 𝐫𝐞𝐝𝐮𝐜𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 𝐚𝐧𝐝 𝐜𝐨𝐨𝐫𝐝𝐢𝐧𝐚𝐭𝐢𝐨𝐧 in distributed apps.
A fun way to look at this is similar to the idea of Turning the Database Inside Out - like Turning the Microservice Inside Out.
The core idea is: Applications coordinate with many systems (DBs, queues, locks, schedulers, ...) which are all logs underneath. But each log independently maintains its ground truth. We lack common order and conditions.
By letting all those logs build on top of a common log, we can make a lot of distributed systems problems in apps and microservices virtually disappear.
But how is this practically usable, given that our DBs and queues aren't built like this? How do we strike a sweet-spot balance between this model with its great resilience and consistency, and maintaining healthy decoupling and separation of concerns?
We wrote about that design pattern, how it inspired our work on @restatedev, and how you can adopt this for your architecture.
👇
𝐄𝐯𝐞𝐫𝐲 𝐒𝐲𝐬𝐭𝐞𝐦 𝐢𝐬 𝐚 𝐋𝐨𝐠
An idea on how to drastically 𝐫𝐞𝐝𝐮𝐜𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 𝐚𝐧𝐝 𝐜𝐨𝐨𝐫𝐝𝐢𝐧𝐚𝐭𝐢𝐨𝐧 in distributed apps.
A fun way to look at this is similar to the idea of Turning the Database Inside Out - like Turning the Microservice Inside Out.
The core idea is: Applications coordinate with many systems (DBs, queues, locks, schedulers, ...) which are all logs underneath. But each log independently maintains its ground truth. We lack common order and conditions.
By letting all those logs build on top of a common log, we can make a lot of distributed systems problems in apps and microservices virtually disappear.
But how is this practically usable, given that our DBs and queues aren't built like this? How do we strike a sweet-spot balance between this model with its great resilience and consistency, and maintaining healthy decoupling and separation of concerns?
We wrote about that design pattern, how it inspired our work on @restatedev, and how you can adopt this for your architecture.
👇
@chrija@nathanbenaich Clear case for a multi-agent LLM system. Let's just have a virtual meeting where the notary AI reads out the financing documents via text-to-speech and all stakeholders' agents transcribe it back, process and re-negotiate if necessary. Best deals negotiating last minute changes!
@andreasklinger The magic word is “Bezugsurkunde” - instead of unproductively sitting around for hours (or even for days), rather have the notary read everything out to his/her own employees; then just sweep in for a 5 minute chat to give your blessing to the sacred ritual that had happened. 🚀