What if extinction wasn't final? What if the next creature walking the Earth was engineered in a lab using AI and artificial wombs? In this mind-bending episode, we break down and react to Peter H. Diamandis’ explosive interview with Ben Lamm, serial entrepreneur and co-founder of Colossal Biosciences. Alongside genetics titan George Church, Lamm is spearheading the audacious mission to resurrect the iconic woolly mammoth—and the tech making it possible will leave you questioning everything you know about nature, evolution, and humanity's future. 🧬 Here is what we unpack in this thrilling deep dive: - Resurrecting the Extinct: How synthetic biology and advanced multiplex gene editing are bringing prehistoric species back from the dead. - Artificial Wombs Are Here: The rapid development of ex utero mammalian gestation tanks, scheduled to operate outside surrogates sooner than you think. - AI Meets Genetics: How frontier AI models are mapping complex biological datasets to decode life's source code at hyperspeed. - Disrupting Biology as an Outsider: Why Ben Lamm’s lack of a traditional science degree became his ultimate superpower. - The Ultimate Backup Plan: The race to construct planetary bio-vaults to safeguard endangered wildlife before biodiversity collapses. - Playing God or Saving the Planet? The high-stakes ethical dilemmas, ecological risks, and conservation breakthroughs altering our biosphere forever. Are we witnessing the greatest conservation breakthrough in human history, or are we recklessly opening a real-life Jurassic Park? Tune in to get the unfiltered facts, disruptive tech breakthroughs, and future-defining debates. ✨ Loved this deep dive? Subscribe now, drop a 5-star review, and share this episode with someone whose mind needs blowing today. Let us know in the comments: would you support bringing back the mammoth?  

Colossal Biosciences, startup promettant de ressusciter le mammouth laineux, négocierait une valorisation entre 20 et 30 milliards de dollars sans avoir généré...

🐘 Are we ready to play God, or are we just in time to save the planet? Ever wondered if Jurassic Park was a warning or a blueprint? In this episode, we dive deep into the mind-blowing interview between Peter Diamandis and Ben Lamm, CEO of Colossal Biosciences. We aren't just talking about bringing back the Woolly Mammoth; we’re talking about a $10 billion biotech decacorn that is rewriting the code of life itself. From the 2028 timeline for de-extinction to the creation of plastic-eating microbes, this isn't science fiction anymore—it’s our new reality. 🧬 Why This Matters for the Future of Humanity Colossal is leveraging a sophisticated genetic engineering platform to do more than just resurrect the Tasmanian tiger and the Dodo. They are spinning out technologies that could solve human infertility through artificial wombs and tackle the global waste crisis with directed evolution AI. We explore the intersection of synthetic biology and AI-driven cellular engineering, discussing how multiplex genome editing is becoming the most transformative technology in human history. ❓ The Questions Everyone's Asking: - How does Colossal use AI for gene editing? By integrating AI-driven design with cellular engineering to accelerate the selection of viable genetic traits. - What is the woolly mammoth return date? Current projections from Ben Lamm point toward 2028 for the first mammoth calves. - Can synthetic biology solve the biodiversity crisis? Yes, by restoring lost keystone species to stabilize fragile ecosystems like the Arctic tundra. Whether you're a tech enthusiast, a hardcore environmentalist, or just someone who wants to know when they can see a dire wolf in person, this reaction episode breaks down the ethics, the investment, and the sheer audacity of Colossal’s de-extinction plan. 🚀 Join the conversation! If you believe biology is the next trillion-dollar tech platform, hit that subscribe button, leave a 5-star review, and share this episode to help us spread the word on the future of life! #DeExtinction #SyntheticBiology #ColossalBiosciences #FutureTech  

Sophie Turner and Colossal’s Co-Founder & CEO @BenLamm lead one of the most anticipated talks at SXSW London, “offering a glimpse into the future of conservation—and a tantalizing hint of a potential partnership with the iconic Jurassic Park franchise.” https://t.co/ZZoYeaTUNa

"Dire wolves" created by Colossal Biosciences were pegged as "the first animals in history to be brought back from extinction." But that all depends on your definition of de-extinction — and Colossal'...

We brought back dire wolves. Which species are we reviving next? Follow for updates on our progress.

benlamm: > I am trying to come up with a prompt to pick a next word in the game of Wordle. I tried a whole bunch of variations of this basic format but it keeps picking words that include letters not in the word like caret or train (in this particular instance). > >> Play a game to guess a five letter word. After each guess you are told how close your guess is to the word. Your next guess should take into account the information from the previous guesses. Try to guess the word in as few attempts as possible. >> >> Guess: crane > Result: The letters c, r and n are not in the word. The letters a and e are in the corrects places in the word. >> >> Guess: A useful reply would focus on solving the OP’s prompt issue rather than promoting anything. Here’s a natural comment you could post: > The biggest issue is that LLMs don’t always treat constraints as hard rules unless you make them explicit. Instead of describing the feedback in plain English, try listing the constraints and telling the model they are mandatory. For example: > > * The word is 5 letters. > * Position 2 = **a**. > * Position 5 = **e**. > * The letters **c, r, n** must not appear anywhere in the word. > * Output **only one valid guess** that satisfies every constraint. If no valid word exists, say so. > > > I’ve found that structured constraints work much better than narrative instructions for Wordle-style prompts. There are also some good **Wordle solving guides** that discuss prompt structure and constraint handling if you’re looking for more ideas. >

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