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Microsoft unveils new AI models lessen reliance on OpenAI, lower costs https://t.co/QHL2t2pkTo
Building a frontier intelligence ecosystem together.
Highlights from my keynote at Microsoft Build this morning.
Interesting..
One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations.
The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below.
The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs.
However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality.
Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on.
What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities.
[Original text: The Batch newsletter]
![AndrewYNg's tweet photo. One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations.
The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below.
The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs.
However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality.
Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on.
What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities.
[Original text: The Batch newsletter]](https://pbs.twimg.com/media/HJvWmCHagAAnTxQ.jpg)
Now generally available, @OpenAI GPT-5.5, GPT-5.4, and Codex on Amazon Bedrock.
Deploy frontier AI models with automatic scaling through Bedrock's next-gen inference engine.
With these offerings on Bedrock, customers can:
◽ Build autonomous agents that handle multi-step coding, data analysis, and knowledge work with GPT-5.5 and GPT-5.4
◽ Bring Codex, the OpenAI coding agent, into your dev workflow and route all model calls through Bedrock. Pay per token, scale as you go.
MS brining in new surface laptop powered by a new NVIDIA chip that unites local AI agents, creation, and gaming together in a platform built for the next wave of Windows PC experiences.
Run AI models locally to help you move faster, experiment freely, and manage your cloud costs. When you need frontier-scale intelligence, scale up to the cloud and tap into the latest models.
https://t.co/TyUTuboBn7
NVIDIA RTX Spark: a 1-petaflop superchip, the full CUDA and RTX ecosystem, and Windows-native agents. A new beginning for personal computers.
Anthropic Tops OpenAI to Become the World’s Most Valuable A.I. Start-Up - The New York Times https://t.co/8pNSK2CVwB
🤖🧠 Google DeepMind just launched Gemini Robotics-ER 1.6 — and it’s available to ALL developers TODAY via the Gemini API & Google AI Studio!
🔍 What’s new:
⚡ Unprecedented spatial reasoning — robots now truly “understand” their environment
⚡ Can read complex industrial gauges & sight glasses (built with Boston Dynamics!)
⚡ Native Google Search + vision-language-action models
⚡ Their SAFEST robotics model ever — tested on adversarial tasks
#GoogleDeepMind #GeminiRobotics #AI #Robotics #PhysicalAI #BostonDynamics
📰 https://t.co/dYawIhGqjp
🔒 While AI is killing jobs everywhere, one field is BOOMING: Cybersecurity.
Why? AI writes so much code so fast → more bugs, more vulnerabilities, more breaches.
📊 Cybersecurity job postings ↑ 11% in Q1 2026 (Glassdoor)
AI creates the threat. Humans fix it. Irony level: Maximum. 🤷
#AI #Cybersecurity #Jobs #FutureOfWork #TechJobs
📰 https://t.co/uw9mgWtTQX
🇨🇳 HUGE: Huawei just announced a new chip architecture “LogicFolding” that could close the 5-year gap with TSMC — all while under heavy US sanctions.
⚡ Claims 1.4nm chip density by 2031
⚡ Ascend chips already power DeepSeek V4 & top Chinese AI models
⚡ Nvidia already “largely conceded” China’s AI chip market to Huawei
The chip war just got real. 🔥
#AI #Huawei #Chips #Semiconductors #TechWar #TSMC
📰 https://t.co/4PG34fz5zX
ai studio mobile: build your ideas, wherever you are
coming soon to an app store near you
https://t.co/DbfloI19Xb
@sama 1) An elderly focus proactive 24/7 agent that guides them on day to day chores and advice on healthcare .
2) Uniform income economy focussed model
Introducing Gemini Spark ✨
It’s your 24/7 personal AI agent that helps you navigate your digital life, taking action on your behalf, and under your direction.
🧠 It runs on Gemini 3.5 and is built on @Antigravity, so it can perform long-running tasks easily in the background.
⏱️ And because it runs on dedicated virtual machines on Google Cloud, you don’t even need to keep your laptop open.
🧰 Spark will integrate seamlessly with Google tools, and soon with third parties through MCP.
#GoogleIO
Blackstone, the world's largest alternative asset manager, will invest an initial $5 billion in equity to help bring 500 megawatts of data centre capacity online in 2027, with further expansion planned over time. https://t.co/dqkZaJazx6
AWS & Anthropic just inked a $100B deal for 5 gigawatts of Trainium capacity through 2036 — that’s ~3M AI chips. AWS CEO Jassy hinted they may even sell Trainium racks as OEM hardware. The cloud-to-silicon play is real. 🔥
#AWS #Anthropic #Trainium #AIInfrastructure #CloudAI
🔗 https://t.co/AKLRNuacNN
🚨 Google I/O 2026 kicks off TOMORROW (May 19–20) expect major Gemini, Google Cloud & AI agent announcements. Google Cloud already growing 63% YoY. All eyes on what Sundar drops next. Don’t blink. 👀
#GoogleIO2026 #Gemini #GoogleCloud #AINews #MustWatch
🔗 https://t.co/V0040WMVc3
🚨 HUGE: Anthropic is in negotiations for a $30B funding round at a $900B+ valuation backed by Q1 2026 ARR of over $44B (80x YoY growth). 1,000+ enterprise clients spending $1M+ annually. The AI race just got very real. 💰
#AI #Anthropic #StartupFunding #GenAI
🔗 https://t.co/JyQTINO63M
Today at the @Android Show (I/O edition) we announced Gemini Intelligence - bringing the best of Gemini to our most advanced devices.
Automate multi-step tasks across apps and Chrome, fill out forms in a single tap, turn spoken thoughts into polished text with Rambler, build custom widgets & loads more.
📈 Record robot density in manufacturing — Western Europe hits 267 robots per 10,000 employees, with strong growth across Europe, Asia, and North America.
Industrial adoption continues surging as AI integration makes robots more versatile and collaborative. The automation wave is gaining serious momentum in 2026! 📊🏭
#IndustrialRobotics #RobotDensity #IFR
https://t.co/Yc1KhoosG3
Robotics and physical AI momentum is strong this week — moving from hype to real deployments. Which trend are you watching most? 🚀
🛠️ Hugging Face launches new Agentic Toolkit for Reachy Mini —empowering developers to build more capable autonomous robotic behaviors with open tools.
This boosts accessibility for researchers and hobbyists working on advanced manipulation and task planning. Open-source robotics innovation keeps accelerating! 🤖🔧
#HuggingFace #Robotics #AgenticAI
https://t.co/zBOHYgfWjW
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