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Why Tokenization Could Be the Most Important Economic Innovation of Our Lifetime | Bruce Fenton @BruceFenton is a longtime Bitcoin advocate since 2012, securities professional, and one of the early pioneers of tokenized securities. He is the founder and CEO of Chainstone Labs and founder of Atlantic Financial. Alongside Overstock founder @PatrickByrne, Bruce was involved in some of the earliest efforts to bring securities and financial-market infrastructure onto blockchain rails. In 2018, he tokenized equity in his own company, Chainstone Labs, on the Ravencoin blockchain—years before tokenization became one of Wall Street’s biggest narratives. In this episode, Bruce breaks down naked short selling, the plumbing behind traditional securities markets, and why he believes much of the problem is ultimately a ledger problem. We dive into questions such as: Who actually owns the stocks sitting in your brokerage account? How can shares be lent and rehypothecated? What role do brokers, clearing firms, DTCC, and Cede & Co. play in determining who owns what? And could blockchain replace an opaque system of claims and intermediaries with a transparent ledger showing exactly where an asset is and who owns it? We unpack what “tokenized stocks” actually means—and the important distinction between a token that simply gives you exposure to a stock’s price and a security issued natively onchain, where the token itself represents the actual share and the ownership rights that come with it. Bruce discusses how tokenization could allow smaller businesses to tokenize ownership and have their stock traded globally without needing to be listed on a traditional exchange like the NYSE, as well as what a future without KYC could look like. Finally, we get into Wall Street’s embrace of tokenization, the SEC’s evolving approach to tokenized securities, and one of the biggest questions surrounding the future of this technology: who ultimately controls these new financial rails? Remember to subscribe and hit the bell “🔔” icon to get notifications 0:00 Bruce Fenton & Patrick Byrne: Pioneers of Tokenized Securities 3:36 Naked Short Selling Explained 6:28 Who Actually Owns the Stocks in Your Brokerage Account? 12:00 Tokenization Solves Wall Street’s “Ledger Problem” 15:48 What Are You Actually Buying With Robinhood’s Tokenized Stocks? 16:48 Real Tokenized Stocks: When the Token IS the Share 21:46 Tokenization Could Open U.S. Markets to the Entire World 22:52 Why Companies May No Longer Need the NYSE 26:29 Could Tokenized Markets Exist Without KYC? 29:31 Bruce Tokenized Equity on Ravencoin in 2018 30:53 Will Blockchain Make Clearing Houses & DTCC Obsolete? 33:17 Could Tokenization Have Prevented the GameStop Crisis? 38:19 Wall Street Is Embracing Tokenization — Who Gets the Power? 40:20 The SEC’s New Tokenized Securities “Innovation Exemption” 42:57 Why Robinhood’s Tokenized Stocks Don’t Qualify 47:01 Could Everything Eventually Be Tokenized? 51:02 The Dystopian Side of Tokenization: Surveillance & Asset Seizure

When I first saw JEV, as a former TikTok MLE, I knew modern recommendation and search systems could be revolutionized if it keeps evolving. JEV brings general-purpose semantic reasoning into a discriminative inference paradigm: arbitrary context in, calibrated structured decisions out. That matters because recommendation and search are exactly the kinds of decision systems that need to be both smart and fast. Times are changing. Here’s one example: with JEV + Perfectly, we use a complex query to understand AI researchers through their papers across a pool of 500 ECCV 2026 researchers, while achieving the same performance as one of Claude’s models.

Today, Pioneer Labs is announcing our first step towards terraforming Mars. 🚀🌼 With equipment that fits in just a single rocket launch, we can convert Martian dirt, water, and air into enough building materials to construct a small city on Mars. To do it, we made the first microbe for Mars. We found the best microbe on Earth and used evolution to teach it how to source all of its nutrients directly from Martian materials. The first astronauts will be greeted with safe shelter already filled with water, oxygen, and rocket fuel for the return journey. This is the first step toward using biology to make Mars a friendly place for life. It lets us live off the land and helps us build the next great frontier. It's the first of five organisms we need to green Mars ⬇️

ByteDance dropped a banger paper on self-evolving agent harnesses! HarnessDev evaluates whether AI agents can build a runnable harness from scratch and iteratively improve it using execution feedback. Most agent benchmarks keep the harness fixed and only evaluate the model inside it. HarnessDev changes the target of evaluation itself. The agent starts from a minimal seed, builds the harness around the task, runs it, observes what worked or failed, and then modifies that harness across multiple iterations. That means the agent is not only solving the task. It is also changing the planning, memory, tool use, state management, and execution logic around itself. The paper evaluates this in two stages: • Creation: can the model build a complete runnable harness from a minimal starting point? • Evolution: can it improve that harness using feedback from previous runs? The interesting part is that runnable does not automatically mean better. Some generated memory and state mechanisms existed in the code but were barely used during execution, and improvements on visible feedback did not always transfer to held-out tasks. Only 34 of 64 harness changes moved in the same direction on both visible feedback and held-out evaluation, and only 2 of 9 final harness versions were actually the best-performing version on the held-out set. So the paper is really exposing a new challenge: Agents can already start modifying the infrastructure they run on. The harder part is making sure those changes actually generalize. I've shared the paper in the comments!

agents with goldfish memory were getting kinda old so we shipped evolve one click and your agent reviews its past runs keeps the signals that actually mattered writes them back into memory then carries that context into the next run same agent more context less relearning the same lesson evolve is live on neotrade

Introducing the next evolution in LLM text generation: the first fully-fledged serving system built around a decode megakernel. Delivering up to 1.58x faster performance than vLLM. Built for North Mini Code, completely open-source.

.@Giants Coach John Harbaugh and NFL Chief Medical Officer Dr. Allen Sills sat down to discuss player health & safety and how the approach to caring for and protecting players has evolved over the years.

Interesting split in @okx X-Perp activity: Crypto is still highly concentrated: • BTC: 55.6% • ETH: 14.3% • SOL: 5.1% → Top 3 = 75% of crypto volume Equities are much more diversified: • SNDK: 22.8% • SPCX: 18.7% • BEAT: 15.1% → Top 3 = 56.6% Meanwhile, gold dominates metals at 70.7%, while CL accounts for 69.4% of commodity volume. Nice to see OKX evolving into more than just a crypto venue. Try it via my affiliate link: