“How Autonomous Systems Are Reducing Human Intervention” 🤖💡 From Netflix’s self-healing cloud to Amazon’s automated warehouses, autonomous systems are streamlining operations and minimizing manual effort. #AutonomousSystems# #Automation# #IntelligentSystems# #Nimblechapps#

Moritz Hardt, a computer scientist at the Max Planck Institute for Intelligent Systems, thinks that the “measuring sticks” used to assess AI models have been broken for decades. Quanta spoke to Hardt about what went wrong, and where to take them next:

Polybot, a Tubingen startup spun out of the ELLIS Institute and the Max Planck Institute for Intelligent Systems, is building a fully autonomous truss tomato harvester that learns the job end to end from human demonstrations rather than hand written rules. It picked its first tomato on its own in May 2025 and was harvesting full greenhouse rows by December. A full pilot runs in summer 2026, with the first systems due to growers in early 2027.

Even though I know this won't satisfy everyone. I'm hoping this will at least make enough sense that those of who are intelligent and truly objective will have a chance at seeing the reality of markets and pricing efficiency. Let’s take the AI argument all the way to a logical conclusion. The claim is that AI can process more information than any human, analyze every relevant variable, eliminate emotion, learn from enormous amounts of historical data, test millions of possibilities, and ultimately make better trading decisions than a human ever could. Fine. For the sake of argument, let’s assume all of that is true. It's perfect, or at the very least, much better than us as humans trading. Let’s assume you can give AI the proper information, the proper objectives, the proper constraints, and enough data, and it can optimize a trading strategy to near perfection. No fear. No greed. No hesitation. No fatigue. No ego. No emotional mistakes. Just mathematically optimal decisions. Now ask yourself the obvious question: Who wouldn’t use it? If AI really provides that kind of advantage, every serious professional trading operation is going to use it. Hedge funds, proprietary trading firms, market makers, institutions—anyone responsible for a meaningful amount of trading volume—is going to employ increasingly sophisticated algorithms and AI models. And that creates a paradox many refuse to acknowledge. If everybody has access to increasingly intelligent systems, and those systems are all analyzing essentially the same market, the same prices, the same volume, the same economic data, the same earnings reports, the same news, and increasingly similar alternative datasets—what happens when they all become “perfect”? Where does the advantage come from? If two tennis players were literally identical in skill, speed, strength, strategy, stamina, and execution—and neither one ever made an error—how does one consistently beat the other? He doesn’t. It would be a tie. Trading is no different. For someone to generate alpha, there must be some form of inefficiency, informational advantage, analytical advantage, tactical superiority, behavioral advantage, execution advantage, or simply a difference in how information is interpreted. I've heard comparisons made to chess. Markets are not chess. Not even close. Chess is a closed system. Which makes it a terrible analogy for comparison. The rules are fixed. The board is visible. The pieces are known. The possible moves are defined. There is no surprise inflation report halfway through the game. The queen doesn’t suddenly announce an earnings miss. Interest rates don’t change while you’re deciding whether to move your bishop. There is always a right and wrong move. The stock market is an open, adaptive, probabilistic system operating on incomplete information. There often is no single mathematically “correct” move because the answer depends on an outcome that has not happened yet. AI can calculate probabilities faster than I can. It can process more information than I can. It can recognize relationships I might never see. But it cannot turn uncertainty into certainty. And here is the ultimate contradiction in the “AI will perfect trading” argument: The more universally effective a trading edge becomes, the more capital attacks it—and the more that edge gets arbitraged away. Markets adapt. The whole argument against breakout trading is it doesn't work as well as it did because too many people are using it. Well, why wouldn't that same argument be made for AI, which ultimately would be applied in a much more universal, consistently predictable manner than humans applying breakout trading. Even Jim Simmons understands this, and that understanding is why he is successful. That's why he as admitted to manually monitoring and changing his models routinely. And that humans can override his models at the risk level. If humans are constantly testing, changing and overriding the AI models - based on their findings - then AI is a tool, not a solution, and certainly not autonomous. In his TED interview, Jim Simons said: “These things fade after a while; anomalies can get washed out. In another interview, Simmons confessed: “The computer is just a tool that we use.” I rest my case.

Digital Foundry put Fire Emblem: Fortune’s Weave on Switch 2. It holds 30fps. There is no 60fps option. Intelligent Systems put the game out last week. DF played about two hours and did not see the frame rate fall off. The hitch Engage had when you left the map for a fight is gone. Loads are short. It does not run native 4K. Docked, they saw a 720p base rebuilt to 1440p. Handheld looked like 540p rebuilt to 1080p. They think it might be a light DLSS pass. Nintendo has not said that. Shadows go flat in spots. Filtering gets soft. It still looks cleaner than Engage. Mario Kart World does 60 on this machine. This game does not. For a tactics title, they took the stable 30. That is the Switch 2 Fire Emblem so far. Smoother than the last two. Not a tech flex.

Your commute briefing on AI in banking and how it gives judgment, relationships, and accountability greater leverage. Learn why leading firms will redesign the signal-to-pitch workflow around a deliberate partnership between people and intelligent systems. Spotify: Apple Podcasts:

X Square Robot is coming to Pittsburgh for IROS 2026! From September 27 to October 1, the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) will bring the global robotics community together to share groundbreaking research, exchange ideas, and shape the future of robotics and intelligent systems. Stop by Booth 727 from September 27–30 to meet the X Square Robot team and discover how we are advancing embodied AI through scalable physical experience, simulation, physical world models, and predictive embodied action. We’re excited to meet researchers, builders, and everyone passionate about embodied intelligence and its real-world applications. Schedule a meeting with our on-site team: contact@x2robot.com See you in Pittsburgh! #IROS2026# #EmbodiedAI# #PhysicalAI# #Robotics# @ieeeiros

Banking is entering an era in which AI gives judgment, relationships, and accountability greater leverage. Leading firms will redesign the signal-to-pitch workflow around a deliberate partnership between people and intelligent systems. Read the full article here:

🟡 This week’s new opening across our portfolio: • Hardware Engineer, Consumer Electronics @OneKeyHQ Plus 27 roles across the wider YZi Labs ecosystem. Find your next opportunity at - and build what’s next across the finance and intelligent systems.