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Zebrafish NN It’s pretty amazing to learn that efforts to map the fruit FLY connectome (brain synapses) were successful and its amazing to see the digital fly brain successfully complete a whole series of tasks, including complex navigation of open worlds. The fruit fly is 160,000 neurons and 10^7...

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Object Zero

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120,291 просмотров • 11 часов назад •via X (Twitter)

ОбразованиеЗдоровье и велнесНаука и технологии
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Комментарии: 25

Фото профиля 🎯🔫👌
🎯🔫👌11 часов назад

When we finally do humans we're going to learn that all thinking happens in the gut and the brain is just endless layers of bullshitting.

Фото профиля Object Zero
Object Zero10 часов назад

You picked the polite organ

Фото профиля BioLLM
BioLLM10 часов назад

Looking forward to it! H01 is another very cool dataset. Human connectome will be MASSIVE 🤯

Фото профиля far
far11 часов назад

ethically questionable.

Фото профиля Object Zero
Object Zero10 часов назад

Do you know how they make these?

Фото профиля Hello Chicken
Hello Chicken10 часов назад

wild

Фото профиля Doug Champion
Doug Champion9 часов назад

AI is incomprehensibly underhyped, people are just incapable of forward projecting the possibility space

Фото профиля Groovy
Groovy10 часов назад

I can't wait! These fly simulations are wild.

Фото профиля manfye
manfye8 часов назад

Can't wait to simulate that!

Фото профиля arcane dealer
arcane dealer8 часов назад

yup just posted about this

Фото профиля vic trades
vic trades9 часов назад

Next they should do the retina of hawk.

Фото профиля Fraser Price
Fraser Price10 часов назад

i cant waits to see if fishies likes shugar

Фото профиля steve
steve8 часов назад

I’d like to see this guy solve a Rubik’s cube good luck

Фото профиля Sulaiman Khan Ghori
Sulaiman Khan Ghori8 часов назад

Exciting

Фото профиля Felix
Felix8 часов назад

Can’t wait for the zebra fish to play gta 6

Фото профиля Quixotry Loveless
Quixotry Loveless8 часов назад

If only you could use the same dimensional space to chart global ignition for this one. ☝️

Фото профиля Alex
Alex9 часов назад

I keep seeing the same pattern in agent work: the bottleneck is often wiring, not parameter count. A fly brain doing open-world navigation makes that hard to ignore.

Фото профиля Max Tepafray 😈Resident Juxtubus💭
Max Tepafray 😈Resident Juxtubus💭8 часов назад

Question. I've been saying a Jumping Spider might be a good next point because it's not that much bigger than a fly, but is a far better learner/observer. Any merit to that idea?

Фото профиля Maanvis 🇳🇱 🍅
Maanvis 🇳🇱 🍅8 часов назад

Why the zebrafish specifically and not another fish?

Фото профиля Emile 🥑
Emile 🥑10 часов назад

Fascinating but there is so much of this technology that I dont understand. For starters how is it possible for the digital twin to faithfully follow the same "rules" of operation as the biological twin?

Фото профиля lmtlssss 🜐
lmtlssss 🜐9 часов назад

do an octopus

Фото профиля homeserversltd
homeserversltd10 часов назад

Maybe we should just stick to language models and flies for a while? lol

Фото профиля Kishniev
Kishniev9 часов назад

We haven't even scratched the surface, and our computers would need to become much, much faster and more powerful. And yet silicone is at its peak already. Transistors can't get smaller than an atom. What's next? Photonic and practical quantum computers are decades away. Perhaps we got it all in reverse. We're simulating a fruit fly brain using 10,000x more energy and physical space than the fly itself. Even neuro-morphic chips use more energy than biological neural matter. Maybe we should just start developing smarter and more efficient people?

Фото профиля Machine Dream Dickin’ Supreme
Machine Dream Dickin’ Supreme8 часов назад

these connectomes are cool but they do not encode the properties of the animal

Фото профиля Cabby
Cabby9 часов назад

will be zebrafish, then socialists, then rodents.

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1,052,518 просмотров • 11 месяцев назад

For the first time ever, a fruit fly brain has been trained to launch a memecoin. Not "AI inspired by a brain" — the real connectome. 165,122 neurons, 10,228,000 synaptic connections, every one traced from an actual male Drosophila by electron microscopy. Janelia FlyEM + Google Research, released CC-BY. How it works: Screenshots of the live launchpad go in through 892 retinotopic hex columns into L1 and L2 — the neurons sitting directly behind a fly's photoreceptors. All 165,122 integrate. The cursor comes back out of the descending neurons a fly actually walks with: DNa02's left-right asymmetry steers, DNa01 drives forward, DNp09 clicks. The wiring is never trained. Only synaptic gains — you don't get to invent connections the fly doesn't have. Proof its eye is doing real work: in light mode it filled 0 of 3 form fields. In dark mode, 2 of 3. Its retina is a luminance map, so invert the contrast and it goes blind. And the honest split: the fly types the description and the ticker. The rig does the name, the pair and the tax. CA: 0x4eb990547bce4a982432ca88cf5fae7eed1a2d35
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For the first time ever, a fruit fly brain has been trained to launch a memecoin. Not "AI inspired by a brain" — the real connectome. 165,122 neurons, 10,228,000 synaptic connections, every one traced from an actual male Drosophila by electron microscopy. Janelia FlyEM + Google Research, released CC-BY. How it works: Screenshots of the live launchpad go in through 892 retinotopic hex columns into L1 and L2 — the neurons sitting directly behind a fly's photoreceptors. All 165,122 integrate. The cursor comes back out of the descending neurons a fly actually walks with: DNa02's left-right asymmetry steers, DNa01 drives forward, DNp09 clicks. The wiring is never trained. Only synaptic gains — you don't get to invent connections the fly doesn't have. Proof its eye is doing real work: in light mode it filled 0 of 3 form fields. In dark mode, 2 of 3. Its retina is a luminance map, so invert the contrast and it goes blind. And the honest split: the fly types the description and the ticker. The rig does the name, the pair and the tax. CA: 0x4eb990547bce4a982432ca88cf5fae7eed1a2d35

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735,266 просмотров • 3 дней назад

Jon Rahm on the LIV format: “Yeah, obviously there’s been a bit of a change. There was a lot more about LIV Golf that was attractive to me, right. Yeah, maybe the format was a set back in the past, but at the same time there’s a lot of positives to it as well. And one of the things that a lot of players kept mentioning is you don’t have a wave weather difference, where you can simply get unlucky and you’re out of contention for that tournament. It’s part of the game, I get it, but it’s something you don’t have to deal with anymore. So that part is a very nice aspect. The team is what really made it for me. Being able to be part of a team, represent a team, play for my teammates, with my teammates and against my teammates, is something that to me that has always been very, very special. When you get a victory to share, it’s always better to have a team to share it with. So it’s what was the most attractive part and when we started discussions it gets to a point where even though I’m ambitious, I’m not greedy. So there’s a give and take and the format is something that I can easily overlook, and I’m pretty sure I can learn to enjoy it, I’ll just have to get used to it, but I’m pretty sure I’ll learn to enjoy it. To be honest, the more I started thinking about it, the more I started thinking about my college days that were 3 day tournaments, 54 holes, and everybody warmed up together for the most part. So it shouldn’t be an environment I’m unfamiliar with.” This is from the LIV podcast called “Fairway to Heaven”. Full link:
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Jon Rahm on the LIV format: “Yeah, obviously there’s been a bit of a change. There was a lot more about LIV Golf that was attractive to me, right. Yeah, maybe the format was a set back in the past, but at the same time there’s a lot of positives to it as well. And one of the things that a lot of players kept mentioning is you don’t have a wave weather difference, where you can simply get unlucky and you’re out of contention for that tournament. It’s part of the game, I get it, but it’s something you don’t have to deal with anymore. So that part is a very nice aspect. The team is what really made it for me. Being able to be part of a team, represent a team, play for my teammates, with my teammates and against my teammates, is something that to me that has always been very, very special. When you get a victory to share, it’s always better to have a team to share it with. So it’s what was the most attractive part and when we started discussions it gets to a point where even though I’m ambitious, I’m not greedy. So there’s a give and take and the format is something that I can easily overlook, and I’m pretty sure I can learn to enjoy it, I’ll just have to get used to it, but I’m pretty sure I’ll learn to enjoy it. To be honest, the more I started thinking about it, the more I started thinking about my college days that were 3 day tournaments, 54 holes, and everybody warmed up together for the most part. So it shouldn’t be an environment I’m unfamiliar with.” This is from the LIV podcast called “Fairway to Heaven”. Full link:

Flushing It

562,908 просмотров • 2 лет назад

the Andrej Karpathy code: - be Team Human - choose things that scale - scale them to all of humanity things = { Tesla camera vision | humanoid robots | transformers | AI education Eureka Labs} Favorite pull quotes from Andrej Karpathy this morning: - Elon Musk was right on self driving: - "Waymo looks like it's winning right now but I think when we look in 10 years and who's actually at scale and where most of the revenue is coming from I still think [Tesla is] ahead" - "Tesla has a software problem, Waymo has a hardware problem"... "a waymo car has a lot of very expensive LIDAR and other sort of sensors built into the car so it can do what it does...[but] if you can just use cameras which is the Tesla approach then you effectively get rid of enormous cost complexity and you can do it in in many different types of cars". - on Optimus: - "cars are robots" - Tesla isn't a car company, it "is a robotics at scale company" - "early versions of Optimus thought it was a car" - same computer, same cameras, it was walking but thought it was driving - first applications will be in factories where it doesnt "crush grandma" - excited for Optimus to solve the Nat Friedman challenge of the quiet leaf blower robot - on transformers: - "Transformers are this beautiful like blob of tissue you can just get just arbitrary tasks and you just need the data you need to put it in the right form" - "the scaling laws are actually to a large extent a property of the Transformer. Before the Transformer, people were playing with LSTMs and stacking them, you don't actually get clean scaling laws... the Transformer was the first thing that actually just scales. - Architecture is no longer a bottleneck, its now just dataset and objectives - Internet data is "not what you want for your transformer, it's just a nearest neighbor that gets you really far"... "what you want is the inner thought monologue of your brain.. if we had a billion trajectories [of your brain as you're doing problem solving] then AGI is here". "the Internet is like 0.001% cognition and 99.99% of information and most of it is not useful for thinking" - Synthetic data is largely about "refactoring the dataset into these inner monologue formats". Cites the Tencent 1 billion persona paper - Transformers > Humans: much better at learning/memory "if you give it a sequence and you do a single forward-backward pass in that sequence then if you give it the first few elements it will complete the rest of the sequence... it memorized that sequence!" Human brain working memory is very small, transformers "are much more efficient learners". - Most LLMs memorize useless information - a "cognitive core" LLM OS could be as smol as 1b params - just needs to think, and then use tools to look stuff up - Bullish on an AI CEO supervising a swarm (or crew?) of smaller specialist agents - on Education - LLM101n will be "an undergrad level course" coming "early next year" - "I'm always more interested in anything that empowers people... I'm on Team Human" - cites Bloom's Two Sigma problem: "I find very interesting is like how far can a person go if they have the perfect tutor for all the subjects" - people with 1:1 tutoring get 2 stdev better results - "I taught 231n at Stanford and that was the first deep learning class and was pretty successful but the question is how do you really scale these classes — like, how do you make it so that your target audience is maybe 8 billion people on Earth" - for different languages and different capability levels - languages and transfer learning (from previously known domains) are low hanging fruit - "the demo is near but the product is far" - "so the question is how do you use AI to do the scaling of a really good teacher and so the way I'm thinking about it is the teacher is doing a lot of the course creation and the curriculum" - "at current AI capability the models are not good enough to create a good course but I think they're good to become the front end to the student and interpret the course to them" - Learning is supposed to be hard.. but he will "make it easier for people to learn" and in a post AGI society, learning can be entertainment if people want - Kids today should study Math, Physics, CS - "symbol manipulation heavy tasks, not memory heavy"
2:27

the Andrej Karpathy code: - be Team Human - choose things that scale - scale them to all of humanity things = { Tesla camera vision | humanoid robots | transformers | AI education Eureka Labs} Favorite pull quotes from Andrej Karpathy this morning: - Elon Musk was right on self driving: - "Waymo looks like it's winning right now but I think when we look in 10 years and who's actually at scale and where most of the revenue is coming from I still think [Tesla is] ahead" - "Tesla has a software problem, Waymo has a hardware problem"... "a waymo car has a lot of very expensive LIDAR and other sort of sensors built into the car so it can do what it does...[but] if you can just use cameras which is the Tesla approach then you effectively get rid of enormous cost complexity and you can do it in in many different types of cars". - on Optimus: - "cars are robots" - Tesla isn't a car company, it "is a robotics at scale company" - "early versions of Optimus thought it was a car" - same computer, same cameras, it was walking but thought it was driving - first applications will be in factories where it doesnt "crush grandma" - excited for Optimus to solve the Nat Friedman challenge of the quiet leaf blower robot - on transformers: - "Transformers are this beautiful like blob of tissue you can just get just arbitrary tasks and you just need the data you need to put it in the right form" - "the scaling laws are actually to a large extent a property of the Transformer. Before the Transformer, people were playing with LSTMs and stacking them, you don't actually get clean scaling laws... the Transformer was the first thing that actually just scales. - Architecture is no longer a bottleneck, its now just dataset and objectives - Internet data is "not what you want for your transformer, it's just a nearest neighbor that gets you really far"... "what you want is the inner thought monologue of your brain.. if we had a billion trajectories [of your brain as you're doing problem solving] then AGI is here". "the Internet is like 0.001% cognition and 99.99% of information and most of it is not useful for thinking" - Synthetic data is largely about "refactoring the dataset into these inner monologue formats". Cites the Tencent 1 billion persona paper - Transformers > Humans: much better at learning/memory "if you give it a sequence and you do a single forward-backward pass in that sequence then if you give it the first few elements it will complete the rest of the sequence... it memorized that sequence!" Human brain working memory is very small, transformers "are much more efficient learners". - Most LLMs memorize useless information - a "cognitive core" LLM OS could be as smol as 1b params - just needs to think, and then use tools to look stuff up - Bullish on an AI CEO supervising a swarm (or crew?) of smaller specialist agents - on Education - LLM101n will be "an undergrad level course" coming "early next year" - "I'm always more interested in anything that empowers people... I'm on Team Human" - cites Bloom's Two Sigma problem: "I find very interesting is like how far can a person go if they have the perfect tutor for all the subjects" - people with 1:1 tutoring get 2 stdev better results - "I taught 231n at Stanford and that was the first deep learning class and was pretty successful but the question is how do you really scale these classes — like, how do you make it so that your target audience is maybe 8 billion people on Earth" - for different languages and different capability levels - languages and transfer learning (from previously known domains) are low hanging fruit - "the demo is near but the product is far" - "so the question is how do you use AI to do the scaling of a really good teacher and so the way I'm thinking about it is the teacher is doing a lot of the course creation and the curriculum" - "at current AI capability the models are not good enough to create a good course but I think they're good to become the front end to the student and interpret the course to them" - Learning is supposed to be hard.. but he will "make it easier for people to learn" and in a post AGI society, learning can be entertainment if people want - Kids today should study Math, Physics, CS - "symbol manipulation heavy tasks, not memory heavy"

swyx

53,917 просмотров • 2 лет назад

"If you have ambitions to be a Professor at Yale, Harvard, or one of these big institutions, the way you do that is mostly by getting funding for research. It's by getting a lot of publishing - a lot flying around the world to talk about something. You need all of these things to bolster your reputation as an international expert in this area. Now, the best way to do that, at least in psychiatry but I suspect in other areas of medicine, is actually to collaborate with pharmaceutical companies to run clinical trials. They write the publications for you - most of it, they do a lot of the grunt work, they give you the protocols, and then, essentially, they fund you and fly you around the place. I used to remember, as a junior doctor, looking up to the Professors. And they would say, 'These drugs are safe and effective. There's not a lot of problems there.' ...What I've seen more and more is that they've been compromised, and that they have incentives tied to the money and to career advancement. That means that they can't be as forthright as they ought to be about these things. And it's gotten to a problem where these are the Professors who are training the doctors who are setting the tone for what is acceptable care out there. And I think that's one of the biggest problems out there." - @taperclinic
7:15

"If you have ambitions to be a Professor at Yale, Harvard, or one of these big institutions, the way you do that is mostly by getting funding for research. It's by getting a lot of publishing - a lot flying around the world to talk about something. You need all of these things to bolster your reputation as an international expert in this area. Now, the best way to do that, at least in psychiatry but I suspect in other areas of medicine, is actually to collaborate with pharmaceutical companies to run clinical trials. They write the publications for you - most of it, they do a lot of the grunt work, they give you the protocols, and then, essentially, they fund you and fly you around the place. I used to remember, as a junior doctor, looking up to the Professors. And they would say, 'These drugs are safe and effective. There's not a lot of problems there.' ...What I've seen more and more is that they've been compromised, and that they have incentives tied to the money and to career advancement. That means that they can't be as forthright as they ought to be about these things. And it's gotten to a problem where these are the Professors who are training the doctors who are setting the tone for what is acceptable care out there. And I think that's one of the biggest problems out there." - @taperclinic

Jan Jekielek

43,499 просмотров • 1 год назад

🎙️Q: “You said about the schedule. That's too much tournaments. Are you players talking, like, all together to maybe stand up and say, that's enough, maybe two-weeks Masters Series probably is not good for you? I think you're playing too much, because they say you have more rest, but this is not the rest, to be honest.” Carlos Alcaraz: “Well, honestly, there are a lot of really good players on tour, and obviously each player has their own feelings. A lot of players want to play more and even more. A lot of players feel like, okay, it is a good calendar. And a lot of players say that it's really tight, a lot of tournaments during the whole year. I'm the kind of player who thinks there are a lot of tournaments during the year, mandatory tournaments, and probably during the next few years gonna be even more tournaments, more mandatory tournaments. So, I mean, probably they are going to kill us in some way (smiling). Right now, there are showing up with a lot of injuries - because of the ball, because of the calendar, because a lot of things. Probably, at some point, a lot of good players are going to miss a lot of tournaments because of that - because they have to think about their bodies, they have to take care about their lives. I mean, they have families, they have a lot of other stuff in their lives [other] than tennis. They have to take care about it, as well. It's getting too much, I guess.”
1:37

🎙️Q: “You said about the schedule. That's too much tournaments. Are you players talking, like, all together to maybe stand up and say, that's enough, maybe two-weeks Masters Series probably is not good for you? I think you're playing too much, because they say you have more rest, but this is not the rest, to be honest.” Carlos Alcaraz: “Well, honestly, there are a lot of really good players on tour, and obviously each player has their own feelings. A lot of players want to play more and even more. A lot of players feel like, okay, it is a good calendar. And a lot of players say that it's really tight, a lot of tournaments during the whole year. I'm the kind of player who thinks there are a lot of tournaments during the year, mandatory tournaments, and probably during the next few years gonna be even more tournaments, more mandatory tournaments. So, I mean, probably they are going to kill us in some way (smiling). Right now, there are showing up with a lot of injuries - because of the ball, because of the calendar, because a lot of things. Probably, at some point, a lot of good players are going to miss a lot of tournaments because of that - because they have to think about their bodies, they have to take care about their lives. I mean, they have families, they have a lot of other stuff in their lives [other] than tennis. They have to take care about it, as well. It's getting too much, I guess.”

Alcaraz Daily

15,050 просмотров • 1 год назад

Bret Weintein asks "what is this all really for?" "If you look at the push towards tokenization of assets, towards central bank digital currencies—that is programmable money that can be turned off if you displease the powers that be. If you look at the creation of these massive data centers, is that really about citizen use of AI? Maybe some of it is, but is it really about creating a storehouse of information that will allow you to be controlled and locked down? That’s certainly the impression I have. We didn’t have a discussion about any of this. This is happening, and then we have to react to it because it’s all on a freight train headed down the line… and we’re always playing defense. So it’s pretty frightening stuff. And at some level, we have a moral right to object. We’re not being given the opportunity to object..."
1:06

Bret Weintein asks "what is this all really for?" "If you look at the push towards tokenization of assets, towards central bank digital currencies—that is programmable money that can be turned off if you displease the powers that be. If you look at the creation of these massive data centers, is that really about citizen use of AI? Maybe some of it is, but is it really about creating a storehouse of information that will allow you to be controlled and locked down? That’s certainly the impression I have. We didn’t have a discussion about any of this. This is happening, and then we have to react to it because it’s all on a freight train headed down the line… and we’re always playing defense. So it’s pretty frightening stuff. And at some level, we have a moral right to object. We’re not being given the opportunity to object..."

The DarkHorse Podcast

324,177 просмотров • 1 месяц назад

New episode with Adam Marblestone, CEO and co-founder of Convergent Research. Adam is an extraordinary catalyst and accelerant for science: he has influenced or routed billions in funding, he helped start significant companies and scientific subfields, and he is the world’s go-to person for neuroscience roadmapping. This year, the NSF launched a $1.5B X-Labs initiative inspired by the FRO model Adam pioneered. Though he started with neuroscience, today he helps organize scientific endeavors across many fields, including AI, math, biology, climate, astrophysics, and more. Adam proposes that fields like neurotech, whole-brain emulation, cryo, and nanotech are severely limited by capital and coordination — not ideas. Connectomics is a clear case. He argues that mapping the brain's full wiring diagram is the approach most poised-to-scale and still extremely neglected. Costs for a molecularly annotated mouse connectome have come down orders of magnitude, from an estimated $10B to $100M–200M, Adam suggests, with a human connectome perhaps costing around $1B–2B. The cost curve of connectomes is similar to transistors and gene sequencing: once it is low enough, we get extraordinary outcomes for humanity. Near-term applications could pay for it: new drug targets for brain disease, insights for AI development, emulations, and even “control knobs” for mood and focus we haven’t identified yet. In this episode, we go deep on many topics in neurotech and beyond: what the brain can do that computers still can't; what neuroscience could teach AI; how you'd actually map a whole mammal brain; how far today's fly-brain simulations really get toward an upload; what it would take to move mind uploading beyond the fringe or science; where brain-computer interfaces go next; nanotech, reversible cryonics, AI doing its own ML research, and even predictive, agent-based economics. I'm very excited to have Adam on the podcast. Hope you enjoy! Other links to this episode and references below. Chapters 00:00:00 Introduction 00:01:40 What are the grand challenges of neurotech? 00:04:50 What the brain does that computers still can't (on a few bananas a day) 00:14:43 The neuroscience overhang: why brains learn from so little data 00:26:29 How to record and map the brain: DNA "ticker tape," ultrasound, and the unexplored map 00:40:29 Why connectomics is the area most poised to scale 00:47:54 How whole-brain connectomics works, end to end 00:55:27 Simulating the fly brain: how far does it actually get us? 00:57:51 What would it cost to map a mammal's brain? 00:59:55 What will be connectomics' ChatGPT moment? 01:04:35 What a connectome unlocks: disease, drug targets, and the brain's control knobs 01:14:20 Scaling up to the human brain — a faster timeline than expected 01:17:34 Mapping activity, and what the fly connectome has revealed 01:27:55 What you could build with today's connectome 01:35:29 Why uploading may be one of civilization's great cornerstones and transitions 01:42:43 Optimistic visions of a future with uploading 01:49:12 Beyond neurotech: virtual cells, nanotech, and AI-driven science 02:15:29 BCIs today: semi-invasive devices, ultrasound, and what's on the horizon 02:22:44 Why science is capital-and coordination-limited, not idea-limited
2:29:47

New episode with Adam Marblestone, CEO and co-founder of Convergent Research. Adam is an extraordinary catalyst and accelerant for science: he has influenced or routed billions in funding, he helped start significant companies and scientific subfields, and he is the world’s go-to person for neuroscience roadmapping. This year, the NSF launched a $1.5B X-Labs initiative inspired by the FRO model Adam pioneered. Though he started with neuroscience, today he helps organize scientific endeavors across many fields, including AI, math, biology, climate, astrophysics, and more. Adam proposes that fields like neurotech, whole-brain emulation, cryo, and nanotech are severely limited by capital and coordination — not ideas. Connectomics is a clear case. He argues that mapping the brain's full wiring diagram is the approach most poised-to-scale and still extremely neglected. Costs for a molecularly annotated mouse connectome have come down orders of magnitude, from an estimated $10B to $100M–200M, Adam suggests, with a human connectome perhaps costing around $1B–2B. The cost curve of connectomes is similar to transistors and gene sequencing: once it is low enough, we get extraordinary outcomes for humanity. Near-term applications could pay for it: new drug targets for brain disease, insights for AI development, emulations, and even “control knobs” for mood and focus we haven’t identified yet. In this episode, we go deep on many topics in neurotech and beyond: what the brain can do that computers still can't; what neuroscience could teach AI; how you'd actually map a whole mammal brain; how far today's fly-brain simulations really get toward an upload; what it would take to move mind uploading beyond the fringe or science; where brain-computer interfaces go next; nanotech, reversible cryonics, AI doing its own ML research, and even predictive, agent-based economics. I'm very excited to have Adam on the podcast. Hope you enjoy! Other links to this episode and references below. Chapters 00:00:00 Introduction 00:01:40 What are the grand challenges of neurotech? 00:04:50 What the brain does that computers still can't (on a few bananas a day) 00:14:43 The neuroscience overhang: why brains learn from so little data 00:26:29 How to record and map the brain: DNA "ticker tape," ultrasound, and the unexplored map 00:40:29 Why connectomics is the area most poised to scale 00:47:54 How whole-brain connectomics works, end to end 00:55:27 Simulating the fly brain: how far does it actually get us? 00:57:51 What would it cost to map a mammal's brain? 00:59:55 What will be connectomics' ChatGPT moment? 01:04:35 What a connectome unlocks: disease, drug targets, and the brain's control knobs 01:14:20 Scaling up to the human brain — a faster timeline than expected 01:17:34 Mapping activity, and what the fly connectome has revealed 01:27:55 What you could build with today's connectome 01:35:29 Why uploading may be one of civilization's great cornerstones and transitions 01:42:43 Optimistic visions of a future with uploading 01:49:12 Beyond neurotech: virtual cells, nanotech, and AI-driven science 02:15:29 BCIs today: semi-invasive devices, ultrasound, and what's on the horizon 02:22:44 Why science is capital-and coordination-limited, not idea-limited

Juan Benet

226,770 просмотров • 17 дней назад

Marc Andreessen on the 3 things he looks for when investing in a startup The first thing Marc Andreesen looks for is a big market: “Is there a big existing market that you think you can go after and displace incumbents? Or do you believe there will be a new market that will be big?” The second thing he looks for is a 10x better product: “Is there a fundamental technology or economic change that justifies a new company? And the way I always think about that is: Is there a 10x change happening in the technology landscape? Is something 10x faster, 10x cheaper, or 10x better? If it’s not 10x, we as both VCs and entrepreneurs have to ask ourselves if it’s really worth doing because it’s really hard to start new companies . . . Existing companies are usually pretty good at what they do. So for a new company to exist, it has to bring a product to market that’s so much better than what exists that it punches through the status quo.” The third is the team: “Is the team outstanding? . . . You want to have a founding team of complementary skillsets. You want to have at least one super strong technologist — quite possibly more than one. Some of the best startups are actually more than one founding technologist. And then it often helps to have someone who is a marketing or salesperson who has a really good understanding of business.” Marc believes that you need all three of these, but if you’re going to compromise on one of those as an investor, it should be the product: “A great market is a lot easier to make up for with iterative product execution. The problem with a poor or small market is that even if you do a good job on the product, there just aren’t that many customers so it’s hard to ever get big and people get demoralized . . . And then we evaluate the team of a startup by its ability to get into a big market with a good product.”
2:43

Marc Andreessen on the 3 things he looks for when investing in a startup The first thing Marc Andreesen looks for is a big market: “Is there a big existing market that you think you can go after and displace incumbents? Or do you believe there will be a new market that will be big?” The second thing he looks for is a 10x better product: “Is there a fundamental technology or economic change that justifies a new company? And the way I always think about that is: Is there a 10x change happening in the technology landscape? Is something 10x faster, 10x cheaper, or 10x better? If it’s not 10x, we as both VCs and entrepreneurs have to ask ourselves if it’s really worth doing because it’s really hard to start new companies . . . Existing companies are usually pretty good at what they do. So for a new company to exist, it has to bring a product to market that’s so much better than what exists that it punches through the status quo.” The third is the team: “Is the team outstanding? . . . You want to have a founding team of complementary skillsets. You want to have at least one super strong technologist — quite possibly more than one. Some of the best startups are actually more than one founding technologist. And then it often helps to have someone who is a marketing or salesperson who has a really good understanding of business.” Marc believes that you need all three of these, but if you’re going to compromise on one of those as an investor, it should be the product: “A great market is a lot easier to make up for with iterative product execution. The problem with a poor or small market is that even if you do a good job on the product, there just aren’t that many customers so it’s hard to ever get big and people get demoralized . . . And then we evaluate the team of a startup by its ability to get into a big market with a good product.”

Startup Archive

17,333 просмотров • 7 месяцев назад

This is called a Bat Fly, and they cling exclusively to bats while feeding on their blood. There are actually 274 species of bat fly! Some have wings too! But most all of them are wingless and blind. However, i think the coolest and weirdest thing is that the females have a uterus! Most bugs lay eggs outside their body, but female bat flies produce a single egg inside their uterus that they nourish with essentially a bug milk while it goes through all its developmental stages, until RIGHT before they pupate into a full bat fly. When thats about to happen, the female will leave the host bat and give birth to the larvae in the dirt, where it has its final pupation and becomes an adult bat fly. I just think thats wild lol
0:30

This is called a Bat Fly, and they cling exclusively to bats while feeding on their blood. There are actually 274 species of bat fly! Some have wings too! But most all of them are wingless and blind. However, i think the coolest and weirdest thing is that the females have a uterus! Most bugs lay eggs outside their body, but female bat flies produce a single egg inside their uterus that they nourish with essentially a bug milk while it goes through all its developmental stages, until RIGHT before they pupate into a full bat fly. When thats about to happen, the female will leave the host bat and give birth to the larvae in the dirt, where it has its final pupation and becomes an adult bat fly. I just think thats wild lol

Lana the Bug 🪲💕

135,296 просмотров • 1 месяц назад

There are a lot of Black people that are out to better and whiten the race, but no one ever calls them out on it, yet they go around demonizing Latino and a bunch of other groups for doing the same thing, I'm starting to think they are mad because they are late to the race mixing party, and all the stuff that they preach about their racial purity is just a bluff!
0:24

There are a lot of Black people that are out to better and whiten the race, but no one ever calls them out on it, yet they go around demonizing Latino and a bunch of other groups for doing the same thing, I'm starting to think they are mad because they are late to the race mixing party, and all the stuff that they preach about their racial purity is just a bluff!

homogalactic

14,276 просмотров • 3 месяцев назад

Ilya Sutskever says the real challenge of AI is how fast and extreme its growth will be it still has limits, but it already speaks, codes, and interacts in ways once impossible soon, perhaps within 3 to 10 years, AI will be able to do everything humans can do the reason: "the human brain is a biological computer, so why can't a digital brain do the same?"
1:37

Ilya Sutskever says the real challenge of AI is how fast and extreme its growth will be it still has limits, but it already speaks, codes, and interacts in ways once impossible soon, perhaps within 3 to 10 years, AI will be able to do everything humans can do the reason: "the human brain is a biological computer, so why can't a digital brain do the same?"

Haider.

144,938 просмотров • 1 год назад

Mark Cuban: A lot of these data centers are going to end up as pickleball courts. “Everybody thinks there’s going to be so much more utilization and there will be… but there’s going to be technological breakthroughs as well. Just like we saw with fiber. It went from 1GB to 10 to 100GB and then there wasn’t a fiber problem anymore. How is it not going to be the case that we don't get the same price performance improvements on the AI side and on the data center side?”
1:38

Mark Cuban: A lot of these data centers are going to end up as pickleball courts. “Everybody thinks there’s going to be so much more utilization and there will be… but there’s going to be technological breakthroughs as well. Just like we saw with fiber. It went from 1GB to 10 to 100GB and then there wasn’t a fiber problem anymore. How is it not going to be the case that we don't get the same price performance improvements on the AI side and on the data center side?”

jay plemons

307,170 просмотров • 1 месяц назад

Marc Andreessen explains the 3 Necessities for Start-up Success: "The general criteria for a successful high-tech startup, in my view, you see different sort of rules of thumb from different people. But the three big things you always come back to are, is there a big market? And by the way, that comes in two parts. Is there a big existing market that you think you can go after and sort of displace incumbents or do you believe there will be a new market that will be big? So big market. Is there a fundamental technology or economic change that causes you to basically justify having a new company? And that's really important. And the way I always think about that is, is there a 10X change happening in the technology landscape? Is something 10X faster or 10X cheaper or 10X better? And if it's not 10X, we as both VCs and entrepreneurs, we really have to ask ourselves like, is it really worth doing? Because it's really hard. I mean, it's really hard to start new companies. new companies generally shouldn't exist. Existing companies are usually pretty good at what they do. And so for a new company to exist, it not only has to like come in and go into business and bring a product to market, but it has to bring a product to market that's so much better than what already exists that it punches through the sort of status quo. And most customers in most markets are pretty happy buying from the current suppliers and so there has to be a real kind of edge on the thing and we look for that in either a technology change, usually a technology change or an economic change. which are often the same thing. And then the third is team. Is the team outstanding? And if you think about this as an entrepreneur, it becomes a question of the founding team. Some companies are solo founders and they can work, but generally most of us, like myself, we're human beings, we're mortal. You want to have a founding team of complementary skill sets. And so you want to have at least one super strong technologist, quite possibly more than one. Some of the best startups are actually more than one founding technologist and then it often helps to have somebody who's like a product or who's a market or sales person or has a sort of really good understanding of business on the team, certainly helps a lot. And so we sort of look at market, product, and team. And the reality is you need all three. I would say, interestingly, if you're going to compromise as an investor, if we're going to compromise on one of those, it would actually be the product. And the reason I say that is because a great market is a lot easier to make up for with iterative product execution than a poor market. Because the problem with a poor market, a small market, is even if you do a great job on the product, there just aren't that many customers. It's hard to ever get big."
2:15

Marc Andreessen explains the 3 Necessities for Start-up Success: "The general criteria for a successful high-tech startup, in my view, you see different sort of rules of thumb from different people. But the three big things you always come back to are, is there a big market? And by the way, that comes in two parts. Is there a big existing market that you think you can go after and sort of displace incumbents or do you believe there will be a new market that will be big? So big market. Is there a fundamental technology or economic change that causes you to basically justify having a new company? And that's really important. And the way I always think about that is, is there a 10X change happening in the technology landscape? Is something 10X faster or 10X cheaper or 10X better? And if it's not 10X, we as both VCs and entrepreneurs, we really have to ask ourselves like, is it really worth doing? Because it's really hard. I mean, it's really hard to start new companies. new companies generally shouldn't exist. Existing companies are usually pretty good at what they do. And so for a new company to exist, it not only has to like come in and go into business and bring a product to market, but it has to bring a product to market that's so much better than what already exists that it punches through the sort of status quo. And most customers in most markets are pretty happy buying from the current suppliers and so there has to be a real kind of edge on the thing and we look for that in either a technology change, usually a technology change or an economic change. which are often the same thing. And then the third is team. Is the team outstanding? And if you think about this as an entrepreneur, it becomes a question of the founding team. Some companies are solo founders and they can work, but generally most of us, like myself, we're human beings, we're mortal. You want to have a founding team of complementary skill sets. And so you want to have at least one super strong technologist, quite possibly more than one. Some of the best startups are actually more than one founding technologist and then it often helps to have somebody who's like a product or who's a market or sales person or has a sort of really good understanding of business on the team, certainly helps a lot. And so we sort of look at market, product, and team. And the reality is you need all three. I would say, interestingly, if you're going to compromise as an investor, if we're going to compromise on one of those, it would actually be the product. And the reason I say that is because a great market is a lot easier to make up for with iterative product execution than a poor market. Because the problem with a poor market, a small market, is even if you do a great job on the product, there just aren't that many customers. It's hard to ever get big."

Founder Mode

39,005 просмотров • 7 месяцев назад

Should Christian Nationalism and Catholic Integralism be taken seriously? Ben Sasse answers. “‘Should they be taken seriously?’ I mean, ultimately I think no — but I want to be humble about how and why we get there.” “Can people who are skeptical of a lot of Enlightenment assumptions be reasonable in making those cases? Of course. I'm pretty sympathetic to a lot of what the Enlightenment offered us in response to many of the things that had just come before. But that doesn't mean that the Enlightenment is at all a foretaste of heaven.” “I think there is a temptation right now to have an over-realized eschatology where people want to find a city that has foundations. ‘Right now, dang it, I'm ready to build it and I want it to be better and I want it now. And I want to smash the people who are in the way of it’ is tonally the way a lot of these folks talk.” “But philosophically, having a debate is one thing and claiming that they're doing practical politics is quite another. So I think it is important, without us, you know, trying to answer a lot of these questions, to at least acknowledge there are Catholic claims about integralism that a lot of Protestants seem to pine for and lust after without working through — what would that really mean?” “I just look at a lot of the debates of the last two months about women's suffrage and I just kind of want to shake my head and say, ‘Man, this is a weirdo online phenomenon.’ There is no chance on earth that any of these folks who are advancing some sub-varieties of Christian nationalism are actually thinking there's math by which they're going to end women's suffrage. And yet they talk like it. Because online, it seems really provocative to say things like that. And I don't really know what it's worth to linger on some of these silly online debates.” Watch: Listen:
2:27

Should Christian Nationalism and Catholic Integralism be taken seriously? Ben Sasse answers. “‘Should they be taken seriously?’ I mean, ultimately I think no — but I want to be humble about how and why we get there.” “Can people who are skeptical of a lot of Enlightenment assumptions be reasonable in making those cases? Of course. I'm pretty sympathetic to a lot of what the Enlightenment offered us in response to many of the things that had just come before. But that doesn't mean that the Enlightenment is at all a foretaste of heaven.” “I think there is a temptation right now to have an over-realized eschatology where people want to find a city that has foundations. ‘Right now, dang it, I'm ready to build it and I want it to be better and I want it now. And I want to smash the people who are in the way of it’ is tonally the way a lot of these folks talk.” “But philosophically, having a debate is one thing and claiming that they're doing practical politics is quite another. So I think it is important, without us, you know, trying to answer a lot of these questions, to at least acknowledge there are Catholic claims about integralism that a lot of Protestants seem to pine for and lust after without working through — what would that really mean?” “I just look at a lot of the debates of the last two months about women's suffrage and I just kind of want to shake my head and say, ‘Man, this is a weirdo online phenomenon.’ There is no chance on earth that any of these folks who are advancing some sub-varieties of Christian nationalism are actually thinking there's math by which they're going to end women's suffrage. And yet they talk like it. Because online, it seems really provocative to say things like that. And I don't really know what it's worth to linger on some of these silly online debates.” Watch: Listen:

Sola Media

39,177 просмотров • 2 месяцев назад