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#Reinforcementlearning Reel by @asset.attire - AI Trading: Epic Fail or Glorious Chaos? X user handed Clawdbot full portfolio access: "Turn this into $1M. No mistakes." Armed with 25 strategies, 3
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@asset.attire
AI Trading: Epic Fail or Glorious Chaos? X user handed Clawdbot full portfolio access: “Turn this into $1M. No mistakes.” Armed with 25 strategies, 3,000+ reports, 12 algos and 24/7 charting—it executed flawlessly. Result? Total wipeout. “But boy was it beautiful.” The Brutal Reality Check This viral 2026 saga exposes AI trading pitfalls: overfitting, volatility traps, tech glitches, and zero human intuition. Bots crunch data at millisecond speeds but flop in unpredictable markets. Latest AI Trading Strategies 2026 sees reinforcement learning agents adapting live to market shifts, multi-agent systems for collaborative trades, and NLP parsing sentiment from news/social for alpha. Hybrid neuro-symbolic models blend deep learning with rule-based risk controls, while quantum-inspired algos optimize high-frequency edges in crypto/DeFi. Capital Partners’ Adoption Surge VC firms and hedge funds like a16z, Sequoia pour billions into AI trading platforms—adoption hit 70% among top partners by Q1 2026. They’re deploying autonomous portfolios with human vetoes, backtesting on synthetic data, and API integrations for real-time oversight. Game-changer ahead, but pair it with smarts. What’s your take? 👇 #trading #capitalmarkets #aitrading #clawdbot #assets @asset.attire
#Reinforcementlearning Reel by @boomingbulls (verified account) - What JPMorgan Is Doing in Algo Trading 1. Strong Electronic Trading Infrastructure JPMorgan has a sophisticated electronic trading platform with a f
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@boomingbulls
What JPMorgan Is Doing in Algo Trading 1. Strong Electronic Trading Infrastructure JPMorgan has a sophisticated electronic trading platform with a full suite of algorithms (e.g., VWAP) and smart order routing (SOR). They also operate their own alternative trading systems (ATS) like JPM-X and JPB-X, enabling internal matching and dark liquidity crossing. In its futures & options business, JP Morgan highlights algorithmic execution, global exchange connectivity, and robust infrastructure. 2. Machine Learning / AI in Execution Their equity trading desk has developed machine-learning models to recommend optimal execution strategies. In FX (foreign exchange), they once launched a “Deep Neural Network” model (called DNA) that used reinforcement learning for decision-making on execution style. However, they phased out that deep learning model for FX in recent years, citing complexity in interpreting the data. 3. Advanced Research & Security-Preserving Tech JPMorgan has an AIgoCRYPT Center of Excellence, working on secure computation, privacy-preserving ML, and cryptographic mechanisms. They are also working on systems like “Prime Match” — a privacy-preserving inventory matching mechanism, enabling secure matching of client orders without exposing sensitive trading information. They even use differential privacy techniques to obfuscate internal “axe” inventory lists (i.e., what they’re willing to buy/sell), balancing transparency and confidentiality. 4. Quantamental Data Services Through a system called JPMaQS (J.P. Morgan Macro-Synergy Quantamental System), the firm processes huge volumes of macroeconomic and quant data (billions of data points) to generate indicators useful for macro systematic strategies. These indicators can be used for building systematic macro trading, backtesting, and even for constructing investible indices. #boomingbulls #JPMorgan #anishsinghthakur #trading #algorithms #market #trading #IndiaGrowthStory #TradingMindset
#Reinforcementlearning Reel by @realvisiontv (verified account) - 🔥 The future of finance is here...(link in bio).⁠ ⁠ Raoul Pal welcomes Emad Mostaque, co-founder of Stability AI and author of "The Last Economy," ba
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@realvisiontv
🔥 The future of finance is here...(link in bio).⁠ ⁠ Raoul Pal welcomes Emad Mostaque, co-founder of Stability AI and author of "The Last Economy," back to explore how AI is triggering the Economic Singularity. They discuss the potential for a deflationary shock, the rise of digital assets, and the collapse of traditional economic models as humanity transitions from a scarcity-based system to one driven by abundance and machine intelligence. Recorded on October 13, 2025⁠ ⁠ • 🤖 AI Power Players: The people who learn to use AI — not just talk about it — will dominate their industries. Whether it’s coding for a few hours a day or building smarter systems, these innovators will shape the future. 💼⚙️⁠ • 💥 Markets on the Edge: A new wave of reinforcement learning (RL) AIs is coming, ready to shake up finance like never before. Expect wild market behavior as these systems learn, adapt, and compete in real time. 📉🚀⁠ • 🧠 The AI Prediction Era: With prediction platforms like Polymarket and Kalshi raising billions, and AI already ranking 8th in global forecasting championships, the future is clear — soon, machines will out-predict humans. 🏆💡 What happens when all the traders… are algorithms? 🤔⁠ ⁠ #ArtificialIntelligence #Finance #AIMarkets #RealVision⁠ ⁠ 🔥 Get FREE ACCESS to Real Vision (link in bio)
#Reinforcementlearning Reel by @sineadbovell (verified account) - It's time for Canada to claim its foundational role in the AI story🇨🇦 and earn a return on its investment in world-changing research. The groundb
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@sineadbovell
It’s time for Canada to claim its foundational role in the AI story🇨🇦 and earn a return on its investment in world-changing research. The groundbreaking deep learning revolution—one of the biggest AI breakthroughs of the past 15 years—happened at the University of Toronto. Two of the “Godfathers of AI,” Geoffrey Hinton and Yoshua Bengio, are Canadian, with Bengio holding the title of the most cited scientist in the world. Rich Sutton pioneered the field of reinforcement learning, which is why systems like ChatGPT are able to learn from human feedback. Yann LeCun, now the head of AI at Meta, completed his postdoc at the university of Toronto under Geoffrey Hinton. World-renowned computer scientist @poetofcode has transformed the industry’s technical understanding of bias in AI and changed the way these systems are designed and society’s awareness of the problem.. Just to name a few. Canada has produced some of the greatest minds in the industry.
#Reinforcementlearning Reel by @amazonnews (verified account) - A system that succeeds once is a demo. A system that succeeds every time is a breakthrough. So how do you build AI agents that work reliably? In a n
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@amazonnews
A system that succeeds once is a demo. A system that succeeds every time is a breakthrough. So how do you build AI agents that work reliably? In a new episode of "Making a Mind," Dr. Danielle Perszyk, cognitive scientist at Amazon's AGI Lab, sits down with AI researcher and colleague Deniz Birlikci to explore how reinforcement learning (RL) is transforming AI agents into reliable teammates. 🎧 Listen to episode 4 now on YouTube, Amazon Music, Apple Podcasts and Spotify.
#Reinforcementlearning Reel by @cheddar (verified account) - Woah. 🤯 Humanoid robots are getting pretty human-like. The new Figure 02 robot learned to walk naturally using "Reinforcement Learning." Basically,
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@cheddar
Woah. 🤯 Humanoid robots are getting pretty human-like. The new Figure 02 robot learned to walk naturally using “Reinforcement Learning.” Basically, it figures things out through trial and error.
#Reinforcementlearning Reel by @dev2esh - Follow for Ai/Robotics content Dm for link ⬇️⬇️⬇️⬇️ Beginner Level Python & ML Foundations https://www.youtube.com/playlist?list=PLPTV0NXA_ZSgMaz0
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@dev2esh
Follow for Ai/Robotics content Dm for link ⬇️⬇️⬇️⬇️ Beginner Level Python & ML Foundations https://www.youtube.com/playlist?list=PLPTV0NXA_ZSgMaz0Mu-SjCPZNUjz6-6tN Mathematics for Machine Learning https://www.youtube.com/playlist?list=PLPTV0NXA_ZSiR4_XoR1wy-3bv6J0oZ9Zs Machine Learning Fundamentals https://www.youtube.com/playlist?list=PLMrJAkhIeNNR3sNYvfgiKgcStwuPSts9V Deep Learning Basics https://www.youtube.com/playlist?list=PLMrJAkhIeNNT14qn1c5qdL29A1UaHamjx Introduction to Robotics (Conceptual) https://www.youtube.com/watch?v=FGnAeUXRZ4E Robot Kinematics & Motion (Beginner-friendly) https://www.youtube.com/@ArticulatedRobotics ROS & Robotics Fundamentals https://www.youtube.com/playlist?list=PLLSegLrePWgJudpPUof4-nVFHGkB62Izy Intermediate Level Machine Learning (Reinforcement & Applied ML) https://www.youtube.com/playlist?list=PLPTV0NXA_ZSgMaz0Mu-SjCPZNUjz6-6tN Reading & Understanding AI Research Papers https://www.youtube.com/@aipapersacademy/videos Applied Deep Learning & Vision https://www.youtube.com/playlist?list=PLMrJAkhIeNNQe1JXNvaFvURxGY4gE9k74 Practical Robotics Engineering https://www.youtube.com/@kevinwoodrobotics Neural Networks from First Principles https://www.youtube.com/@AndrejKarpathy Advanced Level Advanced Robotics & Control Systems https://www.youtube.com/playlist?list=PLMrJAkhIeNNR20Mz-VpzgfQs5zrYi085m Deep Learning & AI Systems (Stanford-level) https://www.youtube.com/playlist?list=PLoROMvodv4rNiJRchCzutFw5ItR_Z27CM Reinforcement Learning & Advanced ML https://www.youtube.com/playlist?list=PLZnJoM76RM6IAJfMXd1PgGNXn3dxhkVgI #learnings #ML #education #study #engineering
#Reinforcementlearning Reel by @theinformation (verified account) - What are AI 'Gyms'? Jonathan Siddharth, CEO of Turing, explains: "In an RL [Reinforcement Learning] gym, these enterprise agents go to train. And on
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@theinformation
What are AI 'Gyms’? Jonathan Siddharth, CEO of Turing, explains: "In an RL [Reinforcement Learning] gym, these enterprise agents go to train. And once they train, you get to superintelligence." "[They] are like these, mini world models for business, where the gym itself is a collection of prompts and environment and verifiers." Watch the full episode on https://bit.ly/47O6NXe. #AI #MachineLearning #AIAgents
#Reinforcementlearning Reel by @datasciencebrain (verified account) - 🎓Want to level up your AI & tech skills without spending a dime? Here are 10 industry-recognized certifications you can earn for FREE: ✅ Microsoft -
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@datasciencebrain
🎓Want to level up your AI & tech skills without spending a dime? Here are 10 industry-recognized certifications you can earn for FREE: ✅ Microsoft - Career Essentials in Generative AI → LinkedIn Learning ✅ University of Helsinki - Elements of AI → https://www.elementsofai.com ✅ Google Cloud - Introduction to Generative AI → Google Cloud Skills Boost ✅ Harvard University - CS50's Introduction to AI with Python → https://cs50.harvard.edu/ai ✅ Kaggle - Intro to Machine Learning → https://www.kaggle.com/learn ✅ IBM SkillsBuild - AI Fundamentals (Credly) → https://skillsbuild.org ✅ Hugging Face - Deep Reinforcement Learning → https://huggingface.co/learn These aren't just certificates to add to your resume - they're your ticket to understanding the AI revolution that's reshaping every industry. 💡 Pro tip: Don't just collect certificates. Build projects using what you learn, showcase them on GitHub, and talk about your learnings on LinkedIn. 📌 Save this post and start with ONE certification this week. Which one are you choosing? Drop it in the comments! 👇 . . . . . . [datascienceroadmap, airoles, mlengineerpath, datasciencejobs, analyticscareer, datatechskills, mlopsengineer, dataengineerskills, aiindustrytrends, techlearningguide] #datascience #machinelearning #python #ai #dataanalytics #artificialintelligence #deeplearning #bigdata #agenticai #aiagents #statistics #dataanalysis #datavisualization #analytics #datascientist #neuralnetworks #100daysofcode #genai #llms #datasciencebootcamp
#Reinforcementlearning Reel by @niklastitgemeyer (verified account) - Wissenschaftler von Eon Systems haben gerade das vollständige Gehirn einer Fruchtfliege in einen Computer hochgeladen. Die Daten stammen von einer ech
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@niklastitgemeyer
Wissenschaftler von Eon Systems haben gerade das vollständige Gehirn einer Fruchtfliege in einen Computer hochgeladen. Die Daten stammen von einer echten Fliege. 125.000 Neuronen. 50 Millionen synaptische Verbindungen. Alles nachgebaut – und in einen physisch simulierten Körper übertragen. Was dann passierte, ist schwer zu greifen. Anders als bei KI, wo Intelligenz durch das Lernen von Daten entsteht, wurden hier keinerlei Trainingsdaten verwendet. Niemand hat der Fliege erklärt, wie Laufen funktioniert. Kein Reinforcement Learning. Keine Belohnungssignale. Kein Algorithmus, der Bewegungsabläufe optimiert. Und trotzdem hat sie sich sofort fliegentypisch verhalten. Der simulierte Körper bewegt sich. Nicht weil ein machine learning Algorithmus ihm sagt, wie er sich bewegen soll. Sondern weil das kopierte Gehirn es ihm befiehlt. Zum Vergleich: GPT-4 wurde auf schätzungsweise 1 Billion Tokens trainiert, um Sprache zu „verstehen”. Diese Fliege braucht keine einzige Zeile Trainingsdaten, um zu laufen. Weil das Wissen nicht im Modell steckt. Es steckt in der Struktur des kopierten Gehirns selbst. Das ist der fundamentale Unterschied zwischen KI und Whole Brain Emulation (so nennt sich dieses Forschungsfeld). Keine Annäherung an Intelligenz. Kein statistisches Muster. Eine direkte Kopie biologischer Informationsverarbeitung. Und es wird noch verrückter: Das nächste Ziel ist für das Unternehmen ein Mausgehirn. Etwa 70 Millionen Neuronen. 560-mal komplexer als die Fliege. Danach: das menschliche Gehirn. 86 Milliarden Neuronen. Hunderttausende Milliarden Verbindungen. Es eröffnen sich natürlich sofort Fragen: Was passiert, wenn das gelingt? Ist die Simulation dann bewusst? Hat sie Rechte? Leidet sie? Diese Fragen sind schon bald vlt.nicht mehr auf Black Mirror Episoden und philosophische Debatten begrenzt. Sondern sie könnten irgendwann rechtlich und politisch relevant sein. Heute ist es eine Fliege. Aber dass es irgendwann auch mit menschlichen Hirnen passieren wird, wirkt heute ein bisschen weniger wie Science Fiction als noch gestern. Alle Quellen findet ihr über den Link in der Bio. Und wenn ihr eh schon da seid, folgt gerne rein! @niklastitgemeyer
#Reinforcementlearning Reel by @endeavorgr (verified account) - 🚀 "When you dream of something, you shouldn't ask if it can work - but how you can make it work." Ioannis Alexandros Antonoglou, Co-Founder & CTO of
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@endeavorgr
🚀 “When you dream of something, you shouldn’t ask if it can work - but how you can make it work.” Ioannis Alexandros Antonoglou, Co-Founder & CTO of Reflection AI and former DeepMind researcher, shares how his journey from neuroscience to Reinforcement Learning - from NTUA to Edinburgh, UCL, and DeepMind - shaped the way he thinks about AGI, intelligence, and the future of AI systems. 🎧 Listen on Outliers Podcast: link in bio #outliers #endeavor #ai #reflectionai
#Reinforcementlearning Reel by @promptzi - Meet SkyDreamer, a fully neural-network-driven racing drone from the team at TU Delft. Unlike traditional drones, this AI flies purely on "vision", pr
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@promptzi
Meet SkyDreamer, a fully neural-network-driven racing drone from the team at TU Delft. Unlike traditional drones, this AI flies purely on “vision”, processing raw pixels into motor commands in real-time. It doesn’t just follow a path; it “dreams” its way through the track using reinforcement learning. The wildest part? It actually secured a victory over FPV World Champion Yuki Hashimoto at the A2RL Championship. 🏆 From the racetrack to real-world applications, this is the next evolution of physical AI. 🎥: @microuav / YT

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