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Dan ShaperoComplete201 Oct, 10:3429 Apr 2026
Ryan RoslanskyComplete121 Oct, 10:3316 Jun 2026
Erran BergerComplete181 Oct, 10:3423 Jun 2026
Anthony ChavezComplete11 Oct, 10:3230 May 2026
Matt DerellaComplete151 Oct, 10:3016 Jun 2026
Teuila HansonComplete11 Oct, 10:333 Apr 2026
Raghu HiremagalurComplete11 Oct, 10:331 Apr 2016
Jessica JensenComplete221 Oct, 10:3416 Jun 2026
Blake LawitComplete71 Oct, 10:3317 Jun 2026
Nicole LeverichComplete161 Oct, 10:3518 Jun 2026
Jordan LevyComplete11 Oct, 10:3423 Apr 2025
Mark LoboscoComplete91 Oct, 10:352 Jun 2026
Archana SekharComplete21 Oct, 10:3323 Apr 2025
Hari SrinivasanComplete141 Oct, 10:331 Jun 2026
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A few observations after a couple weeks with the new set of personal agents (Muse, Instinct, OAI, etc.): - These agents are going to save us time by knowing a lot about us. Trust is earned, but even without handing over access to my email, it's clear an… moreA few observations after a couple weeks with the new set of personal agents (Muse, Instinct, OAI, etc.): - These agents are going to save us time by knowing a lot about us. Trust is earned, but even without handing over access to my email, it's clear an agent can simplify booking a restaurant with basic context on my family, what time we eat, our favorite places, etc. - Our agents will know each of us, but will not know everything about the world; for example, which restaurant has a table. So they will need many connectors to the world. - The most important 'ux' element for any site that connects with personal agents will be agent management. When thousands of personal agents call the local sushi restaurants as soon as reservations open, who gets the table, how do you manage no-shows, and how do you even know which agent is real? - There is a whole series of agent management mechanisms that will be developed over the next few weeks/months to solve these problems. - Many places without these mechanisms are going to get flooded by these agents. They can opt out, but will lose demand. So there will be a healthy market for solutions that successfully use AI to manage AI.
254 reactions · 45 comments · 1 repostOpen on LinkedIn
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“Information is the new bid” and many other gems on AI and Advertising from my teammate Tim Frank in conversation with AdExchanger
Tim Frank
AI is changing every layer of the internet: how people discover, evaluate, and ultimately transact. I had a far-ranging conversation about the emerging AI… moreAI is changing every layer of the internet: how people discover, evaluate, and ultimately transact. I had a far-ranging conversation about the emerging AI economy with Allison Schiff at AdExchanger about what that means for brands, publishers, and commerce. We covered: • The three eras of the internet: human, LLM, and agentic, and how that plays out for brand discoverability • How bot traffic overtaking human traffic changes the discovery equation • The reality that information quality is becoming the new bid • That interviewing AI models is an important component of market research • Why open standards, such as the Universal Commerce Protocol are so critical to give AIs the ability to take action The shift can sound abstract, but my family experienced a small version of it this summer. We used AI to find specialty shops in New York based on things we already liked. It narrowed the options and helped us plan. Then we did the human part: walked around, explored, and bought a little more than planned. :) That balance of spending less time navigating complexity and more time enjoying the experience is where this gets interesting. Links: • Article: https://lnkd.in/gBKhTPe5 • YouTube: https://lnkd.in/gR4dsnax
28 reactions · 5 comments · – repostsOpen on LinkedIn
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Matt Derella17 SeptRepost with commentaryAI industry commentary
worth a watch if you want hear directly from the ceo of Anthropic and Marc Benioff talk about the what the leading company in AI is doing about safety by adjusting the pacing of their development.
Salesforce
Live: Dario Amodei x Marc Benioff. The Anthropic co-founder & CEO joins us at Dreamforce for a conversation worth hearing. ☁️
97 reactions · 1 comment · 3 repostsOpen on LinkedIn
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NFL kicks off tonight. So cool to see Seahawks analyst Brian Eayrs and other coaches across the league are using Copilot in Excel on the sidelines this season. Will Excel’s Brian Jones end up being the Seahawks MVP this year 😄 https://lnkd.in/g7EECTE4
253 reactions · 16 comments · 10 repostsOpen on LinkedIn
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Went down the rabbit hole on data centers in space... the crazy thing I didn't realize is that one of the hardest parts is going to be cooling the GPUs. But wait, isn't space cold?!? Yes, but in a vacuum there's no medium for absorbing the heat into the… moreWent down the rabbit hole on data centers in space... the crazy thing I didn't realize is that one of the hardest parts is going to be cooling the GPUs. But wait, isn't space cold?!? Yes, but in a vacuum there's no medium for absorbing the heat into the surrounding area... so you need to radiate it away. This article says that for a 100MW data center, you need 2500 pickleball court size radiators. That sounds like a lot. Super interesting. https://lnkd.in/gJEc2rCS
284 reactions · 55 comments · 7 repostsOpen on LinkedIn
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Satya Nadella
In a world where software has real marginal cost for the first time, how do we ensure frontier benefits are diffused across the entire ecosystem? The key is… moreIn a world where software has real marginal cost for the first time, how do we ensure frontier benefits are diffused across the entire ecosystem? The key is to optimize the cost-to-outcome frontier in real world context. In practical terms, that means using the right model for each task, and optimizing the context, skills, tools, and agent harness around it. This is the motivation behind our MAI model family. These models have been built ground up with clean data lineage and optimized for learning transfer from generalist to specialized skills in enterprise RLEs. We continue to make rapid progress in this pursuit. We can now take saturated frontier capabilities and deliver them at scale and at lower cost through models optimized for high-usage products, while continuing to use frontier models for frontier needs. We are proving this out across our first party products, and thereby creating a template for every other AI native, SaaS, or Enterprise company out there. In our products, frontier models from OpenAI and Anthropic are part of the orchestration system alongside MAI. But the model is only one part of the hill-climbing system. Harness, memory, context, tools, skills, user interactions, etc. all shape the evals and performance of these agentic systems. The other key criteria to ensure that you are in control, is your evals should continue to hill climb even when any given model has been removed. Therefore we build RLEs where models learn inside the product system and are rewarded for completing the tasks customers actually care about. We train models against the actual product harness, interactions, and outcomes they will encounter. And strategically ensure that the harness, memory, context, skills are externalized outside of the model. Product-specific evals and model independence give us the control and a direct hill to climb, and to keep refining until we reach the right quality-cost target. We are now seeing MAI models outperform general-purpose frontier models in many use cases while using a fraction of the tokens. We believe the biggest opportunity is to optimize all of these layers together in the products where the world works every day. And we are beginning to route traffic across our first-party surfaces to MAI whenever our models match or outperform frontier alternatives. We are seeing promising early results across GitHub Copilot, Excel, and Outlook and are beginning to take the same approach across Copilot Chat, PowerPoint, and more. And all these results will only get better as the entire system keeps hill-climbing! What we are doing across our first party products is also what every enterprise customer can be doing in their real world agentic systems with their proprietary evals, their proprietary RLEs, workflows, and context. We are making all this available as part of Foundry and our toolchain. Read more here: https://lnkd.in/gR7UgHkp
Hari Srinivasan14 JulRepost with commentaryAI industry commentary
This feels like a great product. Clear pain points, clear time savings & clear respect for the practitioner. Feels rare in AI products; it's not just our benchmark now shows we can do your whole job. Nice work Drew Bent & team. Good for all of us if this really helps teachers teach.
Drew Bent
Today we’re launching Claude for Teachers, bringing the power of premium Claude and Cowork to every US teacher, for free. It works in the background, while… moreToday we’re launching Claude for Teachers, bringing the power of premium Claude and Cowork to every US teacher, for free. It works in the background, while teachers can focus on what’s most important: time with their students. Teachers have been experimenting with AI for some time, but we at Anthropic kept hearing from teachers about the need for something that was aligned to curriculum and evidence based. I think what the team has built is special in a few ways: 1) A foundation in curriculum and learning science -- Claude for Teachers comes with the Learning Commons connector: academic standards in all 50 states, the prerequisite skills beneath each one, and curriculum context from high-quality providers like Illustrative Math and OpenSciEd. Ask for a lesson on constructing linear functions and Claude pulls the standard, notes the misconceptions students typically hold, and builds the lesson around them. 2) Teaching skills, co-built with nonprofit Learning Commons -- These enable teachers to build lesson plans and differentiate instruction. Importantly, they are built to work well in Cowork, allowing teachers to harness the full agentic capabilities of these models. Teachers can control what they share (past lesson plans, student assessment data, etc) and have Claude automatically work for them each evening. It will help them prepare materials for the next day, tailored to their exact students. 3) Privacy first -- We don’t train on teacher conversations and student information is protected by our terms that are written to comply with FERPA. We worked closely with the American Federation of Teachers to align it with their new gold-standard privacy principles. Randi Weingarten, their president, calls it “a tool designed by and for educators... to give them more time for the human relationships at the heart of learning.” 4) Ecosystem approach -- Nine education connectors are available at launch, connecting to tools loved by teachers like TeachFX, MagicSchool, and Brisk Teaching. We’re also releasing a new free AI Fluency for Teachers course with Teach For America. And we’re taking everything we learned and releasing our Skills and evals as public goods, so everyone can leverage them. There is a whole team to thank, including our partners and teachers. I especially want to call out Sofia Wilson and Alex Kasavin, who co-led this. This started as Sofia’s onboarding project, and Alex was her spin-up buddy. In typical Anthropic fashion, we like to give employees overly ambitious spin-up projects (Claude Code was itself one). This was no exception. From the start, the two of them were laser focused on building the highest quality tools for teachers. And it was Elizabeth Kelly and Daniela Amodei who empowered our team to build a product focused on teachers and learning outcomes, first and foremost. If you’re a teacher, you get Claude for Teachers for free starting today: https://lnkd.in/gfRYVmjj
44 reactions · 1 comment · 1 repostOpen on LinkedIn
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Sumit Chauhan
Knowledge work rarely moves in a straight line. Within Microsoft Copilot, you start something in Word, pull the numbers in Excel, then try to turn it into a… moreKnowledge work rarely moves in a straight line. Within Microsoft Copilot, you start something in Word, pull the numbers in Excel, then try to turn it into a story in PowerPoint. The whole time, you're the one making the calls, reading the context, and deciding what actually matters. That’s why the right model in the flow of work matters! Starting today, OpenAI’s GPT 5.6 is beginning to roll out across Word, Excel and PowerPoint which gives customers the world-class reasoning capabilities in the tools where work gets done. Learn more: https://lnkd.in/gCbKpN72