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NEWS: Rivian haș unveiled its Autonomy chip and Gen 3 Autonomy Computer, which the company says is designed to solve the needs of autonomous driving. Chip: • Mutli-chip module • TSMC 5nm • Neural engine: Rivian designed • 800+ TOPS • In-house designed software stack "RAP1 powers the company’s...

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Sawyer Merritt

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148,029 Aufrufe • vor 8 Monaten •via X (Twitter)

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NEWS: Rivian has announced its autonomy subscription, Autonomy+, launching in early 2026 and priced at $2,500 (one-time) or $50/month. Rivian Gen 3 autonomy platform will include 11 cameras, 5 radars and a front-facing LiDAR. It will be powered by RAP1, Rivian's in-house silicon. Software advancements are coming to the company’s second gen R1 vehicles in the near term with the addition of Universal Hands-Free (UHF), bringing hands-free assisted driving for extended periods: • Available on over 3.5 million miles of roads across the USA and Canada. • Capable of operating off-highway on roads with clearly painted lines. "These features have the potential to make the roads safer, address customer demand and become veritable drivers for the business. We plan to continuously improve the autonomy capabilities of its Gen 2 R1 and future R2 vehicles, with a clear trajectory including point-to-point, eyes off and personal L4."
0:25

NEWS: Rivian has announced its autonomy subscription, Autonomy+, launching in early 2026 and priced at $2,500 (one-time) or $50/month. Rivian Gen 3 autonomy platform will include 11 cameras, 5 radars and a front-facing LiDAR. It will be powered by RAP1, Rivian's in-house silicon. Software advancements are coming to the company’s second gen R1 vehicles in the near term with the addition of Universal Hands-Free (UHF), bringing hands-free assisted driving for extended periods: • Available on over 3.5 million miles of roads across the USA and Canada. • Capable of operating off-highway on roads with clearly painted lines. "These features have the potential to make the roads safer, address customer demand and become veritable drivers for the business. We plan to continuously improve the autonomy capabilities of its Gen 2 R1 and future R2 vehicles, with a clear trajectory including point-to-point, eyes off and personal L4."

Sawyer Merritt

348,113 Aufrufe • vor 8 Monaten

Our new Enhanced Highway Assist is just the beginning. RJ Scaringe rides with VP for Autonomy & AI, James Philbin, to talk about the scalable autonomy platform introduced in Gen 2 Rivian vehicles. How will Rivian get to higher levels of autonomy? It starts with a state-of-the-art, in-house, multimodal perception stack that’s trained using advanced machine learning techniques. The Rivian Autonomy Platform is architected to scale and designed to add capabilities over time. Listen as RJ and James discuss the road ahead for autonomy at Rivian:
1:29

Our new Enhanced Highway Assist is just the beginning. RJ Scaringe rides with VP for Autonomy & AI, James Philbin, to talk about the scalable autonomy platform introduced in Gen 2 Rivian vehicles. How will Rivian get to higher levels of autonomy? It starts with a state-of-the-art, in-house, multimodal perception stack that’s trained using advanced machine learning techniques. The Rivian Autonomy Platform is architected to scale and designed to add capabilities over time. Listen as RJ and James discuss the road ahead for autonomy at Rivian:

Rivian

84,887 Aufrufe • vor 1 Jahr

Rivian CEO RJ Scaringe: "The next 10 years will be the most important period in human history." The full interview: 2:45 Rivian’s big 2026 moment 4:23 The origin of Rivian 6:25 The pivot that changed Rivian 7:21 Rivian’s core mission 9:06 Obsessing over details 9:57 Why R2 matters 12:07 Cutting cost, keeping quality 15:21 One brain, thousands of decisions 18:56 Rivian’s software advantage 19:02 Autonomy and the physical world 20:28 The AI shift in self-driving 23:26 Rivian’s autonomy roadmap 25:26 Training AI from real driving 28:41 R2 as a data machine 29:45 Vision vs LiDAR 35:43 Safety and corner cases 37:35 Fewer cars or more driving? 40:03 Robotaxis vs car ownership 42:21 RJ’s robotics thesis beyond the humanoid hype 47:59 How to raise kids for an unrecognizable future 50:40 The timeline that should worry everyone
54:20

Rivian CEO RJ Scaringe: "The next 10 years will be the most important period in human history." The full interview: 2:45 Rivian’s big 2026 moment 4:23 The origin of Rivian 6:25 The pivot that changed Rivian 7:21 Rivian’s core mission 9:06 Obsessing over details 9:57 Why R2 matters 12:07 Cutting cost, keeping quality 15:21 One brain, thousands of decisions 18:56 Rivian’s software advantage 19:02 Autonomy and the physical world 20:28 The AI shift in self-driving 23:26 Rivian’s autonomy roadmap 25:26 Training AI from real driving 28:41 R2 as a data machine 29:45 Vision vs LiDAR 35:43 Safety and corner cases 37:35 Fewer cars or more driving? 40:03 Robotaxis vs car ownership 42:21 RJ’s robotics thesis beyond the humanoid hype 47:59 How to raise kids for an unrecognizable future 50:40 The timeline that should worry everyone

Matthew Berman

397,688 Aufrufe • vor 5 Monaten

$RIVN $TSLA Now I know why Tesla influencers are mad. Rivian just put a fork in the road for FSD monopoly. First initial reaction after 30 minutes of testing Rivian Universal Hands Free. In the video below, the car is doing all the work on back roads. FYI, Universal Hands Free is not equivalent to FSD yet, but point to point coming out in 2026 should put Rivian right up there. Here is the fork in the road: 1. Claim: Everyone will license FSD from Tesla. Reality: Rivian will release point to point next year. 2. Claim: Everyone is 10 years behind Tesla in autonomous driving. Reality: Rivian is only about 1.5 years behind. 3. Claim: LiDAR is too expensive. Reality: It costs around $200. 4. Claim: Multiple sensors cause confusion and delayed decision making. Reality: With early sensor fusion, there is no confusion or added complexity. 5. Claim: Tesla is the only software defined company. Reality: Rivian licenses its software to VW for $5 billion beating Tesla to it.
1:00

$RIVN $TSLA Now I know why Tesla influencers are mad. Rivian just put a fork in the road for FSD monopoly. First initial reaction after 30 minutes of testing Rivian Universal Hands Free. In the video below, the car is doing all the work on back roads. FYI, Universal Hands Free is not equivalent to FSD yet, but point to point coming out in 2026 should put Rivian right up there. Here is the fork in the road: 1. Claim: Everyone will license FSD from Tesla. Reality: Rivian will release point to point next year. 2. Claim: Everyone is 10 years behind Tesla in autonomous driving. Reality: Rivian is only about 1.5 years behind. 3. Claim: LiDAR is too expensive. Reality: It costs around $200. 4. Claim: Multiple sensors cause confusion and delayed decision making. Reality: With early sensor fusion, there is no confusion or added complexity. 5. Claim: Tesla is the only software defined company. Reality: Rivian licenses its software to VW for $5 billion beating Tesla to it.

MoreGainzs

191,208 Aufrufe • vor 8 Monaten

🚀After Years of building battle-tested autonomy for drones, we’re excited to make JETCORE-FC publicly available ! Our flagship compute module along with Flight control carrier board designed for real-time perception, autonomy, and edge AI workloads. Built around NVIDIA Jetson, JETCORE-FC powers our own drones that fly without GPS, without radio, and without compromise. Now, we’re bringing the same power to the hands of developers, researchers, and system integrators. 🔧 Plug-and-play with: High-speed interfaces for camera, LIDAR, and IMU Ruggedized I/O and low-latency networking Full support for ROS, PX4, and custom Linux pipelines Whether you’re building next-gen robotics, defense-grade UGVs, or intelligent drones, JETCORE-FC gives you the reliability and performance we trust in the field. 🛒 Get yours now → #Vecros #JETCORE #EdgeAI #NVIDIAJetson #Robotics #Autonomy #Drones #AI #GPSTech #DroneComputing #SpatialAI NVIDIA NVIDIA Robotics Rashree Besta prem sai RobuIN
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🚀After Years of building battle-tested autonomy for drones, we’re excited to make JETCORE-FC publicly available ! Our flagship compute module along with Flight control carrier board designed for real-time perception, autonomy, and edge AI workloads. Built around NVIDIA Jetson, JETCORE-FC powers our own drones that fly without GPS, without radio, and without compromise. Now, we’re bringing the same power to the hands of developers, researchers, and system integrators. 🔧 Plug-and-play with: High-speed interfaces for camera, LIDAR, and IMU Ruggedized I/O and low-latency networking Full support for ROS, PX4, and custom Linux pipelines Whether you’re building next-gen robotics, defense-grade UGVs, or intelligent drones, JETCORE-FC gives you the reliability and performance we trust in the field. 🛒 Get yours now → #Vecros #JETCORE #EdgeAI #NVIDIAJetson #Robotics #Autonomy #Drones #AI #GPSTech #DroneComputing #SpatialAI NVIDIA NVIDIA Robotics Rashree Besta prem sai RobuIN

VECROS

15,633 Aufrufe • vor 11 Monaten

ELON MUSK: We believe the AI5 chip will be roughly comparable performance to an NVIDIA Blackwell, and at much less than 10% of the cost Transcription: I'm super hardcore on chips right now as you may be able to tell. I have chips on the brain. I dream about chips, Literally! Because in order to have a functional robot, you have to have a great AI chip. And it needs to be an inexpensive chip and it needs to be very power efficient So we think we believe the AI5 chip will be probably about a third of the power of say something like a Blackwell, an NVIDIA Blackwell, which is a great chip, for roughly comparable performance. And much less than 10% of the cost. This is a chip that is very much optimized for the Tesla AI software stack. So it's not meant to be a general purpose chip, it's meant to be an amazing chip for the Tesla AI software And I mean a couple of things that I think make... like how is Tesla able to achieve such an improvement? I think it is because we are specialized. We're not trying to... you know, NVIDIA has to serve the superset of all past and future customers. So all of their requirements, all of the software that they've written has to work, which is a very difficult problem. Whereas we just need to make it work for our software. And so we're able to simplify the chip dramatically And then we also, I think we're unique in this, but like we have an integer-based system. And integer operations are fundamentally more efficient than floating point operations. So we can do floating point, but the vast majority of our inference is done in integer. Which is, if you're familiar with sort of logic gates, the simplicity of integer... it's integer is much more power efficient, much more silicon efficient, but you have to, you actually have to train for integer inference, which everyone else is training for floating point. That's kind of like a niche technical detail, but it's actually very important. So, yeah, this is going to be a great chip So this chip will be made in basically in four places: TSMC Taiwan, Samsung Korea, TSMC Arizona, and TSMC Texas. And we already know what improvements to make for AI6. So I'm hopeful that we can within less than a year of AI5 starting production, we can actually transition in the same fab to AI6 and double all of the performance metrics
3:12

ELON MUSK: We believe the AI5 chip will be roughly comparable performance to an NVIDIA Blackwell, and at much less than 10% of the cost Transcription: I'm super hardcore on chips right now as you may be able to tell. I have chips on the brain. I dream about chips, Literally! Because in order to have a functional robot, you have to have a great AI chip. And it needs to be an inexpensive chip and it needs to be very power efficient So we think we believe the AI5 chip will be probably about a third of the power of say something like a Blackwell, an NVIDIA Blackwell, which is a great chip, for roughly comparable performance. And much less than 10% of the cost. This is a chip that is very much optimized for the Tesla AI software stack. So it's not meant to be a general purpose chip, it's meant to be an amazing chip for the Tesla AI software And I mean a couple of things that I think make... like how is Tesla able to achieve such an improvement? I think it is because we are specialized. We're not trying to... you know, NVIDIA has to serve the superset of all past and future customers. So all of their requirements, all of the software that they've written has to work, which is a very difficult problem. Whereas we just need to make it work for our software. And so we're able to simplify the chip dramatically And then we also, I think we're unique in this, but like we have an integer-based system. And integer operations are fundamentally more efficient than floating point operations. So we can do floating point, but the vast majority of our inference is done in integer. Which is, if you're familiar with sort of logic gates, the simplicity of integer... it's integer is much more power efficient, much more silicon efficient, but you have to, you actually have to train for integer inference, which everyone else is training for floating point. That's kind of like a niche technical detail, but it's actually very important. So, yeah, this is going to be a great chip So this chip will be made in basically in four places: TSMC Taiwan, Samsung Korea, TSMC Arizona, and TSMC Texas. And we already know what improvements to make for AI6. So I'm hopeful that we can within less than a year of AI5 starting production, we can actually transition in the same fab to AI6 and double all of the performance metrics

X Freeze

305,109 Aufrufe • vor 9 Monaten

ELON MUSK: "The AI 5 chip which is going to be a great chip. All of Tesla hinges on that chip. That's the chip that going to our next gen self driving cars and it's also essential for Optimus. So that chip program was in bad shape. It wasn't on the path to success and we also had the DOJO program which was also doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program to get everyone focused on the AI5 chip. It's performance per watt is extremely good. It is probably going to be at least 2-3 times better than NVIDIA performance per watt and 10% cost of the NVIDIA chip something like that."
1:52

ELON MUSK: "The AI 5 chip which is going to be a great chip. All of Tesla hinges on that chip. That's the chip that going to our next gen self driving cars and it's also essential for Optimus. So that chip program was in bad shape. It wasn't on the path to success and we also had the DOJO program which was also doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program to get everyone focused on the AI5 chip. It's performance per watt is extremely good. It is probably going to be at least 2-3 times better than NVIDIA performance per watt and 10% cost of the NVIDIA chip something like that."

DogeDesigner

265,257 Aufrufe • vor 9 Monaten

ELON: TESLA FUTURE'S HINGES ON THE AI5 CHIP PROJECT "The AI5 chip, which is going to be a great chip, all of Tesla hinges on that chip. That's the chip that is going into our next generation of self-driving cars, and it's also essential for the Optimus robot. So that chip program was in bad shape. It wasn't closing because it's quite an ambitious chip design, and it really wasn't on a path to success. And then we also had the Dojo program, which was doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program, which is to get everyone focused on the AI5 chip, which is essential. Continue to use NVIDIA for training, but we need the AI5 inference chip, which is a very powerful chip, but it's also a very low-power chip. So it doesn't use a lot of power. Its performance per watt is extremely good. I think it's probably going to be at least 2 to 4 times better than NVIDIA performance per watt at the inference level in the car and the robot. And I don't know, 10% of the cost of an NVIDIA chip, something like that. So these are very important numbers to achieve." Source: Elon Musk, Baron Capital, Ron Baron, Tesla
2:09

ELON: TESLA FUTURE'S HINGES ON THE AI5 CHIP PROJECT "The AI5 chip, which is going to be a great chip, all of Tesla hinges on that chip. That's the chip that is going into our next generation of self-driving cars, and it's also essential for the Optimus robot. So that chip program was in bad shape. It wasn't closing because it's quite an ambitious chip design, and it really wasn't on a path to success. And then we also had the Dojo program, which was doing okay but not on a path to be competitive with NVIDIA. So I collapsed the two programs into just one program, which is to get everyone focused on the AI5 chip, which is essential. Continue to use NVIDIA for training, but we need the AI5 inference chip, which is a very powerful chip, but it's also a very low-power chip. So it doesn't use a lot of power. Its performance per watt is extremely good. I think it's probably going to be at least 2 to 4 times better than NVIDIA performance per watt at the inference level in the car and the robot. And I don't know, 10% of the cost of an NVIDIA chip, something like that. So these are very important numbers to achieve." Source: Elon Musk, Baron Capital, Ron Baron, Tesla

Mario Nawfal

225,142 Aufrufe • vor 9 Monaten

This is where I have to share my raw feelings about Rivian software currently on R1. The software experience they have created is good. It’s their own, with their software stack that they control. With that said, we have to stop making excuses for longstanding bugs. Like Quinn Nelson had posted about long ago, having to do multiple Resets, logins and out to get core functionality to work is not the experience we should be having. I know Rivian and Wassym do not want this. I also know they are working on R2 stuff as well. As a person who has spent real money on 4 Rivian’s with 3 R2 reservation between me and hubby, we are huge fans. Have helped many become Rivian owners as well. But the long outstanding bugs are starting to boil over. It’s dragging the software reliability down. Apple Music has been in Rivian vehicles for just about 2 years now. We are past the stage of it being “new”. Spatial Audio is a key music feature, and for me, and plenty of others, you have to turn that off sometimes just to get music to play. I shouldn’t have to do that. Plus, you can’t change that feature while the vehicle is in drive. So then you have to pull over and fiddle with it just to get it work and sometimes it doesn’t. Rivian assistant can’t do it either. Among other issues, like HVAC preconditioning, unstable cabin temps, GPS locking issues, profile switching not getting right or switching profile after the driver has gotten in, mobile app live activities not functioning properly, and more. The live activities is important, because we don’t have a notification for charging start stop/complete except for charging complete on DCFC, so on a level 2 charger, I don’t know if there is an issue with charging if the live activities don’t appear. Same for HVAC if it’s not showing up I have to keep opening the app to check to see what the temperature is. If you aren’t going to push me a notification that the cabin is at the temp I selected in favor of the live activities, then the live activities has to work. I could go on, but I really love my Rivian. I love the brand, I love what they want to do. And I think R2 is going to change the market for most things, but I want their focus to be on software and stability. Focus on polish, focus on features that many people want, don’t over complicate those things. Example, valet mode should be here by now that locks down speed acceleration and access to certain parts of the vehicle. Basic Pin to drive, not the multi factors drive one that depends on your phone and vehicle having an internet connection. Speedy, clean, stable software is always a win. I know Wassym Bensaid and plenty of others at Rivian can do this. We have seen it before and seen what they can do. The YouTube app is by far the best app they have added. I haven’t had any issues with it. It’s responsive, and works. Everything needs to work like that across the board. Please guy let me help in anyway I can, I just want the best for you and the community and customers. Let’s focus on that. I know some will see this as a complete complaining post but it’s not. It’s a plead to make the experience better for everyone and making the Rivian software the best software it can be.
12:47

This is where I have to share my raw feelings about Rivian software currently on R1. The software experience they have created is good. It’s their own, with their software stack that they control. With that said, we have to stop making excuses for longstanding bugs. Like Quinn Nelson had posted about long ago, having to do multiple Resets, logins and out to get core functionality to work is not the experience we should be having. I know Rivian and Wassym do not want this. I also know they are working on R2 stuff as well. As a person who has spent real money on 4 Rivian’s with 3 R2 reservation between me and hubby, we are huge fans. Have helped many become Rivian owners as well. But the long outstanding bugs are starting to boil over. It’s dragging the software reliability down. Apple Music has been in Rivian vehicles for just about 2 years now. We are past the stage of it being “new”. Spatial Audio is a key music feature, and for me, and plenty of others, you have to turn that off sometimes just to get music to play. I shouldn’t have to do that. Plus, you can’t change that feature while the vehicle is in drive. So then you have to pull over and fiddle with it just to get it work and sometimes it doesn’t. Rivian assistant can’t do it either. Among other issues, like HVAC preconditioning, unstable cabin temps, GPS locking issues, profile switching not getting right or switching profile after the driver has gotten in, mobile app live activities not functioning properly, and more. The live activities is important, because we don’t have a notification for charging start stop/complete except for charging complete on DCFC, so on a level 2 charger, I don’t know if there is an issue with charging if the live activities don’t appear. Same for HVAC if it’s not showing up I have to keep opening the app to check to see what the temperature is. If you aren’t going to push me a notification that the cabin is at the temp I selected in favor of the live activities, then the live activities has to work. I could go on, but I really love my Rivian. I love the brand, I love what they want to do. And I think R2 is going to change the market for most things, but I want their focus to be on software and stability. Focus on polish, focus on features that many people want, don’t over complicate those things. Example, valet mode should be here by now that locks down speed acceleration and access to certain parts of the vehicle. Basic Pin to drive, not the multi factors drive one that depends on your phone and vehicle having an internet connection. Speedy, clean, stable software is always a win. I know Wassym Bensaid and plenty of others at Rivian can do this. We have seen it before and seen what they can do. The YouTube app is by far the best app they have added. I haven’t had any issues with it. It’s responsive, and works. Everything needs to work like that across the board. Please guy let me help in anyway I can, I just want the best for you and the community and customers. Let’s focus on that. I know some will see this as a complete complaining post but it’s not. It’s a plead to make the experience better for everyone and making the Rivian software the best software it can be.

Tyrone Holland🚀🧑🏽‍💻

51,082 Aufrufe • vor 3 Monaten

Doubling down on my $RIVN Investment! Here are all the reasons why: • Founder RJ (RJ Scaringe), an MIT grad, is brilliant, hands-on, and laser-focused on Rivian (not building 7 different companies) • Rivian is the ONLY other company (besides $TSLA) that has already built a full EV stack: - cutting-edge software - top-tier manufacturing - in-house battery tech - in-house electronics & FSD/AI hardware - in-house top-tier AI and full self driving team - in-house fast-charging network (similar to Tesla super chargers) • Rivian is the ONLY other company that is shipping an 8-camera surround view and powerful onboard computer for FSD in EVERY vehicle. They can collect enormous amounts of real-world video (2nd only to Tesla) to train their AI. Can’t believe no traditional car maker is doing this yet! • Rivian’s FSD/AI team is led by top talent making rapid progress on FSD using latest AI neural net techniques, similar to Tesla’s FSD v12+. • Rivian’s R1 Truck and SUV are both highly rated and loved by customers • Rivian’s Delivery van is a unique offering that is also loved by customers • Rivan’s R2 vehicle (to be launched in 2026) is intended to be high-volume and will likely be a great alternative to the Model Y and drive the company to profitability (note that it doesn't need to beat Model Y...the shift is from gas-cars to EVs). • Rivian’s $5.8B parnership with VW proves that Rivian is FAR ahead in software/tech/electronics than any other traditional car company (remember VW is the world’s largest car manufacturer and they still need Rivian’s help for EVs!) • Rivan’s ~$13 Billion market cap is RIDICULOUSLY LOW for a company that is as accomplished with real-world products that customers love. That said, there are RISKS with Rivian: • Scaling & production challenges could delay Rivian’s progress • They are still losing A LOT of money every quarter and if progress to profitability takes too long, they could run out of money and be forced to raise money at unfavorable terms. But if Rivian becomes a viable and profitable company, in say 5 years from now, producing 500K+ vehicles, it could easily have a $200 Billion valuation (less than 1/7th or 15% of $TSLA’s valuation TODAY!) That’s roughly a 1,500% potential upside, with just a 100% downside, making this bet well worth it for me, even if the probability of success is less than 50/50. So that's why I’m doubling down on $RIVN. 🚀
8:19

Doubling down on my $RIVN Investment! Here are all the reasons why: • Founder RJ (RJ Scaringe), an MIT grad, is brilliant, hands-on, and laser-focused on Rivian (not building 7 different companies) • Rivian is the ONLY other company (besides $TSLA) that has already built a full EV stack: - cutting-edge software - top-tier manufacturing - in-house battery tech - in-house electronics & FSD/AI hardware - in-house top-tier AI and full self driving team - in-house fast-charging network (similar to Tesla super chargers) • Rivian is the ONLY other company that is shipping an 8-camera surround view and powerful onboard computer for FSD in EVERY vehicle. They can collect enormous amounts of real-world video (2nd only to Tesla) to train their AI. Can’t believe no traditional car maker is doing this yet! • Rivian’s FSD/AI team is led by top talent making rapid progress on FSD using latest AI neural net techniques, similar to Tesla’s FSD v12+. • Rivian’s R1 Truck and SUV are both highly rated and loved by customers • Rivian’s Delivery van is a unique offering that is also loved by customers • Rivan’s R2 vehicle (to be launched in 2026) is intended to be high-volume and will likely be a great alternative to the Model Y and drive the company to profitability (note that it doesn't need to beat Model Y...the shift is from gas-cars to EVs). • Rivian’s $5.8B parnership with VW proves that Rivian is FAR ahead in software/tech/electronics than any other traditional car company (remember VW is the world’s largest car manufacturer and they still need Rivian’s help for EVs!) • Rivan’s ~$13 Billion market cap is RIDICULOUSLY LOW for a company that is as accomplished with real-world products that customers love. That said, there are RISKS with Rivian: • Scaling & production challenges could delay Rivian’s progress • They are still losing A LOT of money every quarter and if progress to profitability takes too long, they could run out of money and be forced to raise money at unfavorable terms. But if Rivian becomes a viable and profitable company, in say 5 years from now, producing 500K+ vehicles, it could easily have a $200 Billion valuation (less than 1/7th or 15% of $TSLA’s valuation TODAY!) That’s roughly a 1,500% potential upside, with just a 100% downside, making this bet well worth it for me, even if the probability of success is less than 50/50. So that's why I’m doubling down on $RIVN. 🚀

Hamid

93,818 Aufrufe • vor 1 Jahr

David Ulevitch on how AI is transforming energy, defense, and logistics: "If you start at the most fundamental level, energy—we have an insatiable thirst for energy in this country, and AI compute is driving a huge amount of it." "AI compute will then power lots of things. It's not just going to power ChatGPT, but it's going to power autonomy systems, all kinds of other language models, and all other kinds of use cases." "If you look at defense, computer vision is transforming the battlefield." "Then you see AI transforming logistics... flight operations and planning using AI, so you can have the most efficient flight planning, save the most amount of fuel, and make sure that the least amount of flights get canceled." David Ulevitch 🇺🇸 on sourcery
3:30

David Ulevitch on how AI is transforming energy, defense, and logistics: "If you start at the most fundamental level, energy—we have an insatiable thirst for energy in this country, and AI compute is driving a huge amount of it." "AI compute will then power lots of things. It's not just going to power ChatGPT, but it's going to power autonomy systems, all kinds of other language models, and all other kinds of use cases." "If you look at defense, computer vision is transforming the battlefield." "Then you see AI transforming logistics... flight operations and planning using AI, so you can have the most efficient flight planning, save the most amount of fuel, and make sure that the least amount of flights get canceled." David Ulevitch 🇺🇸 on sourcery

a16z

17,567 Aufrufe • vor 6 Monaten

“If we can make AI make better chips, then those chips can power the next generation of AI models.” Startup ‘Ricursive Intelligence,’ founded by Azalia Mirhoseini and Anna Goldie, has been building AI tools to do just that: to speed up the chip design process. The company’s name is a nod to “recursive self-improvement,” the idea that AI could one day bootstrap itself without human involvement. If they’re successful, Goldie and Mirhoseini could revolutionize the way the chip industry works. At the moment, AI companies mostly optimize their models for certain chips. But in a future where chip design happens far faster, it could work the other way around: chips optimized for specific models. The founders are on the TIME100 AI, the list of people shaping the development of AI in 2026. See the full list:
1:12

“If we can make AI make better chips, then those chips can power the next generation of AI models.” Startup ‘Ricursive Intelligence,’ founded by Azalia Mirhoseini and Anna Goldie, has been building AI tools to do just that: to speed up the chip design process. The company’s name is a nod to “recursive self-improvement,” the idea that AI could one day bootstrap itself without human involvement. If they’re successful, Goldie and Mirhoseini could revolutionize the way the chip industry works. At the moment, AI companies mostly optimize their models for certain chips. But in a future where chip design happens far faster, it could work the other way around: chips optimized for specific models. The founders are on the TIME100 AI, the list of people shaping the development of AI in 2026. See the full list:

TIME

38,584 Aufrufe • vor 1 Tag

Before an autonomous machine can act, it has to understand. A construction site is one of the most unpredictable environments imaginable. The terrain changes with every pass. Material piles shift. Other machines move nearby. No two digs are the same. For a human operator, reading that environment is second nature, built from years of experience and constant sensory feedback. Teaching a machine to do the same is one of the hardest problems in autonomy. Scene understanding is how we're working to solve it. Our system fuses LiDAR point clouds, camera feeds, and real-time terrain data into a continuous, three-dimensional picture of everything happening around the machine. It's a living model of the environment, updated moment to moment so the machine can make decisions grounded in what's actually in front of it.
0:31

Before an autonomous machine can act, it has to understand. A construction site is one of the most unpredictable environments imaginable. The terrain changes with every pass. Material piles shift. Other machines move nearby. No two digs are the same. For a human operator, reading that environment is second nature, built from years of experience and constant sensory feedback. Teaching a machine to do the same is one of the hardest problems in autonomy. Scene understanding is how we're working to solve it. Our system fuses LiDAR point clouds, camera feeds, and real-time terrain data into a continuous, three-dimensional picture of everything happening around the machine. It's a living model of the environment, updated moment to moment so the machine can make decisions grounded in what's actually in front of it.

Bedrock Robotics

33,148 Aufrufe • vor 3 Monaten

I HIGHLY recommend watching (or rewatching) the Former Head of Tesla AI Andrej Karpathy brilliantly explain how Tesla’s Vision approach is the answer to Wide-Scale Global Autonomy on Lex Fridman’s Podcast. Quick Summary: • Extra sensors add cost to the system, and more importantly complexity. They make the software task harder, and increase the cost of all the data pipelines. They add risk and complexity to the supply chain and manufacturing. • Vision is necessary to the task (which almost all agree on) and it should also be sufficient as well. If it is sufficient, the cost of extra sensors and tools outweighs their benefit. • Sensors change as parts change or become available and unavailable. They must be maintained and software adapted to these changes. They must also be calibrated to make fusion work properly. • Having a fleet gathering more data is more important than having more sensors. • Using LiDAR can actually be a liability. • Having to process LIDAR and radar produces a lot of bloat in the code and data pipelines. Andrej predicts other companies will also drop these sensors in time. • Mapping the world and keeping it up to date is much too expensive. You won’t change the world with this limitation, you need to focus on vision which is the most important. The roads are designed to be interpreted with vision.
6:26

I HIGHLY recommend watching (or rewatching) the Former Head of Tesla AI Andrej Karpathy brilliantly explain how Tesla’s Vision approach is the answer to Wide-Scale Global Autonomy on Lex Fridman’s Podcast. Quick Summary: • Extra sensors add cost to the system, and more importantly complexity. They make the software task harder, and increase the cost of all the data pipelines. They add risk and complexity to the supply chain and manufacturing. • Vision is necessary to the task (which almost all agree on) and it should also be sufficient as well. If it is sufficient, the cost of extra sensors and tools outweighs their benefit. • Sensors change as parts change or become available and unavailable. They must be maintained and software adapted to these changes. They must also be calibrated to make fusion work properly. • Having a fleet gathering more data is more important than having more sensors. • Using LiDAR can actually be a liability. • Having to process LIDAR and radar produces a lot of bloat in the code and data pipelines. Andrej predicts other companies will also drop these sensors in time. • Mapping the world and keeping it up to date is much too expensive. You won’t change the world with this limitation, you need to focus on vision which is the most important. The roads are designed to be interpreted with vision.

Nic Cruz Patane

234,961 Aufrufe • vor 1 Jahr

DigiPower X CEO michel amar takes you inside the Company’s AI Infrastructure Campus in Columbiana, Alabama, showcasing the technology and infrastructure being deployed for the next generation of high-performance computing and artificial intelligence. The facility features DigiPower X’s ARMS 200 modular infrastructure, designed to support NVIDIA B300 GPUs with advanced direct-to-chip liquid cooling, high-density power delivery, resilient power distribution and modular scalability. Michel highlights the key components behind the deployment, including the IT-load modular system, liquid-cooling infrastructure, switchgear and redundant backup generation designed to support demanding AI workloads. The goal is clear: deploy AI compute faster, more efficiently and at significantly higher density. DigiPower X — Powering Intelligence at Scale. $DGXX $DGX #DigiPowerX #DGXX #AIInfrastructure #DataCenters #ArtificialIntelligence #NVIDIAB300 #NVIDIA #GPUInfrastructure #HighPerformanceComputing #HPC #LiquidCooling #DataCenterInfrastructure #AIDatacenter #DigitalInfrastructure #Alabama
2:53

DigiPower X CEO michel amar takes you inside the Company’s AI Infrastructure Campus in Columbiana, Alabama, showcasing the technology and infrastructure being deployed for the next generation of high-performance computing and artificial intelligence. The facility features DigiPower X’s ARMS 200 modular infrastructure, designed to support NVIDIA B300 GPUs with advanced direct-to-chip liquid cooling, high-density power delivery, resilient power distribution and modular scalability. Michel highlights the key components behind the deployment, including the IT-load modular system, liquid-cooling infrastructure, switchgear and redundant backup generation designed to support demanding AI workloads. The goal is clear: deploy AI compute faster, more efficiently and at significantly higher density. DigiPower X — Powering Intelligence at Scale. $DGXX $DGX #DigiPowerX #DGXX #AIInfrastructure #DataCenters #ArtificialIntelligence #NVIDIAB300 #NVIDIA #GPUInfrastructure #HighPerformanceComputing #HPC #LiquidCooling #DataCenterInfrastructure #AIDatacenter #DigitalInfrastructure #Alabama

DigiPower X

73,202 Aufrufe • vor 11 Tagen

Elon Musk in a new interview this morning on Tesla FSD: "In terms of having self-driving be ubiquitous, I think we’re making steady progress. The Tesla Full Self-Driving software, which is really just AI and cameras, we don’t use radars or LIDAR or anything like that. It’s really trying to drive the car in the same way that a human drives the car, primarily with vision and with a biological neural net. We take the same approach with our vehicles, which is a digital neural net and cameras. I expect this approach to ultimately be at least an order of magnitude safer than humans driving. It is quite magical because the car feels like it is sentient. It actually feels like it’s alive and you can actually, as we improve the software, feel the sentience growing in the car. We already have some vehicles operating with no people inside with no safety monitors in three cities in Texas and probably will be widespread in the US by the end of this year and hopefully in Israel too" Tesla FSD is beginning to feel more and more sentient with each update, it’s incredible. All without the use of Radar or LiDAR. It’s all about the 🧠.
1:47

Elon Musk in a new interview this morning on Tesla FSD: "In terms of having self-driving be ubiquitous, I think we’re making steady progress. The Tesla Full Self-Driving software, which is really just AI and cameras, we don’t use radars or LIDAR or anything like that. It’s really trying to drive the car in the same way that a human drives the car, primarily with vision and with a biological neural net. We take the same approach with our vehicles, which is a digital neural net and cameras. I expect this approach to ultimately be at least an order of magnitude safer than humans driving. It is quite magical because the car feels like it is sentient. It actually feels like it’s alive and you can actually, as we improve the software, feel the sentience growing in the car. We already have some vehicles operating with no people inside with no safety monitors in three cities in Texas and probably will be widespread in the US by the end of this year and hopefully in Israel too" Tesla FSD is beginning to feel more and more sentient with each update, it’s incredible. All without the use of Radar or LiDAR. It’s all about the 🧠.

Nic Cruz Patane

104,268 Aufrufe • vor 3 Monaten

We have recently launched the first “DEEP” underwater drone system in a demonstration mission that marked a significant milestone for our Group in the field of underwater technology. DEEP is designed for the protection, development, and maintenance of critical infrastructure and port areas, while also performing monitoring and environmental protection activities. Thanks to a network of underwater sensors for early warning, a Command and Control Center for real-time operational management, a team of autonomous underwater vehicles capable of conducting missions at different levels of autonomy, cooperation, and coordination, and an Al-based system dedicated to data analysis and processing, we bring on board a dual-purpose and versatile technology able to operate efficiently in diverse contexts. Watch some highlights from DEEP’s missions 👇
0:25

We have recently launched the first “DEEP” underwater drone system in a demonstration mission that marked a significant milestone for our Group in the field of underwater technology. DEEP is designed for the protection, development, and maintenance of critical infrastructure and port areas, while also performing monitoring and environmental protection activities. Thanks to a network of underwater sensors for early warning, a Command and Control Center for real-time operational management, a team of autonomous underwater vehicles capable of conducting missions at different levels of autonomy, cooperation, and coordination, and an Al-based system dedicated to data analysis and processing, we bring on board a dual-purpose and versatile technology able to operate efficiently in diverse contexts. Watch some highlights from DEEP’s missions 👇

Fincantieri

5,294,212 Aufrufe • vor 10 Monaten

Neil Movva (Neil Movva) started his career at Nvidia, working on GPUs and kernels, and has an unusually deep understanding of inference, from software to chips to power. We spend a lot of time on each of those layers, how they connect, and where the important tradeoffs are. What makes this conversation special is how detailed it is (like a 401-level class), yet Neil makes it remarkably clear and easy to follow. Today he runs Sail Research, a company building infrastructure for agents to make tokens as cheap as possible. We discuss: - Latency versus throughput - Why there are no bad chips, only bad pricing - The end of kernel engineering - Buying chips and power no one else wants - New chip architectures - Nvidia lore + his contrarian view of the company - Open source and the frontier labs I learned a ton. Enjoy! TIMESTAMPS 0:00 Intro 0:38 Building a “Token Factory” 4:21 The Future of Background Agents 13:09 Nvidia and the GPU Stack 23:27 Chips, Memory, and Transformers 36:14 The Future of AI Training Data 44:32 Chip Scarcity and Compute Arbitrage 52:44 Reinventing the AI Data Center 59:01 Power and the “Scavenger Strategy” 1:10:10 Open vs. Closed AI
1:23:35

Neil Movva (Neil Movva) started his career at Nvidia, working on GPUs and kernels, and has an unusually deep understanding of inference, from software to chips to power. We spend a lot of time on each of those layers, how they connect, and where the important tradeoffs are. What makes this conversation special is how detailed it is (like a 401-level class), yet Neil makes it remarkably clear and easy to follow. Today he runs Sail Research, a company building infrastructure for agents to make tokens as cheap as possible. We discuss: - Latency versus throughput - Why there are no bad chips, only bad pricing - The end of kernel engineering - Buying chips and power no one else wants - New chip architectures - Nvidia lore + his contrarian view of the company - Open source and the frontier labs I learned a ton. Enjoy! TIMESTAMPS 0:00 Intro 0:38 Building a “Token Factory” 4:21 The Future of Background Agents 13:09 Nvidia and the GPU Stack 23:27 Chips, Memory, and Transformers 36:14 The Future of AI Training Data 44:32 Chip Scarcity and Compute Arbitrage 52:44 Reinventing the AI Data Center 59:01 Power and the “Scavenger Strategy” 1:10:10 Open vs. Closed AI

Patrick OShaughnessy

4,349,881 Aufrufe • vor 3 Tagen