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A potentially high-efficiency alternative to making large genome edits: making large RNA edits via splicing! Very cool proof-of-concept from Jacob Borrajo Kamyab Javanmardi, Ph.D. ⚛️ Basem Al-Shayeb, Ph.D. 🧬 & Blainey Lab in bioRxiv

Julia Bauman

10,421 subscribers

15,348 views • 3 years ago •via X (Twitter)

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3 Comments

Julia Bauman3 years ago

Find the preprint here:

Ahmed Mahfouz3 years ago

@jacobborrajo @Kamyab_J @themicrobeguy @BlaineyLab @biorxivpreprint This looks intersting @oligogirl @PSpitali

Danny Diaz3 years ago

@jacobborrajo @Kamyab_J @themicrobeguy @BlaineyLab @biorxivpreprint @DrJimmyDale check out Kamyab latest work. #grinding

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36,918 views • 4 months ago

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27,897 views • 1 year ago

Groq is serving the fastest responses I've ever seen. We're talking almost 500 T/s! I did some research on how they're able to do it. Turns out they developed their own hardware that utilize LPUs instead of GPUs. Here's the skinny: Groq created a novel processing unit known as the Tensor Streaming Processor (TSP) which they categorize as a Linear Processor Unit (LPU). Unlike traditional GPUs that are parallel processors with hundreds of cores designed for graphics rendering, LPUs are architected to deliver deterministic performance for AI computations. The LPU's architecture is a departure from the SIMD (Single Instruction, Multiple Data) model used by GPUs and favor a more streamlined approach that eliminate the need for complex scheduling hardware. This design allows every clock cycle to be utilized effectively, ensuring consistent latency and throughput. For developers, this means that performance can be precisely predicted and optimized which is critical in real-time AI applications. Energy efficiency is another area where LPUs shine. By reducing the overhead of managing multiple threads and avoiding the underutilization of cores, LPUs can deliver more computations per watt. Groq's innovative chip design allows multiple TSPs to be linked together without the traditional bottlenecks found in GPU clusters making them extremely scalable. This enables linear scaling of performance as more LPUs are added simplifying the hardware requirements for large-scale AI models and making it easier for developers to scale their applications without rearchitecting their systems. So what does this all mean? LPUs could provide a massive improvement compared to GPUs for serving AI applications in the future! If anything it will be great to have alternative high performing hardware since A100s and H100s are so in demand

Groq is serving the fastest responses I've ever seen. We're talking almost 500 T/s! I did some research on how they're able to do it. Turns out they developed their own hardware that utilize LPUs instead of GPUs. Here's the skinny: Groq created a novel processing unit known as the Tensor Streaming Processor (TSP) which they categorize as a Linear Processor Unit (LPU). Unlike traditional GPUs that are parallel processors with hundreds of cores designed for graphics rendering, LPUs are architected to deliver deterministic performance for AI computations. The LPU's architecture is a departure from the SIMD (Single Instruction, Multiple Data) model used by GPUs and favor a more streamlined approach that eliminate the need for complex scheduling hardware. This design allows every clock cycle to be utilized effectively, ensuring consistent latency and throughput. For developers, this means that performance can be precisely predicted and optimized which is critical in real-time AI applications. Energy efficiency is another area where LPUs shine. By reducing the overhead of managing multiple threads and avoiding the underutilization of cores, LPUs can deliver more computations per watt. Groq's innovative chip design allows multiple TSPs to be linked together without the traditional bottlenecks found in GPU clusters making them extremely scalable. This enables linear scaling of performance as more LPUs are added simplifying the hardware requirements for large-scale AI models and making it easier for developers to scale their applications without rearchitecting their systems. So what does this all mean? LPUs could provide a massive improvement compared to GPUs for serving AI applications in the future! If anything it will be great to have alternative high performing hardware since A100s and H100s are so in demand

Jay Scambler

318,228 views • 2 years ago

We are excited to share our #CORL2024 paper on learning quadrotor obstacle avoidance from the visual stream of a single #eventcamera! Trained entirely in simulation! We demonstrate obstacle avoidance both in the dark and in a forest up to 5m/s. PDF: Video: Project page: Event cameras are sensors that output per-pixel-level intensity changes at microsecond latency resolution; they feature nearly zero motion blur and high dynamic range but produce a very large volume of events under significant ego-motion and further lack a high-fidelity continuous-time sensor model in simulation, making direct #sim2real transfer not possible. By leveraging depth prediction as a pretext task, we pre-train a reactive obstacle avoidance policy with “approximated” simulated events and then fine-tune the perception component with limited events-and-depth real-world data. This technique bridges the sim2real gap for #eventcameras! As at the current state, there is no continuous-time sensor model for event cameras, we hope that this work can finally spur future research leveraging simulation for training event-vision-based policies to create faster, agile robots! Kudos to Anish Bhattacharya, @marcocannic, Vijay Kumar Nikolai Matni UZH Science University of Zurich UZH Space Hub UZH IfI European Research Council (ERC) GRASP Laboratory Penn Engineering

We are excited to share our #CORL2024 paper on learning quadrotor obstacle avoidance from the visual stream of a single #eventcamera! Trained entirely in simulation! We demonstrate obstacle avoidance both in the dark and in a forest up to 5m/s. PDF: Video: Project page: Event cameras are sensors that output per-pixel-level intensity changes at microsecond latency resolution; they feature nearly zero motion blur and high dynamic range but produce a very large volume of events under significant ego-motion and further lack a high-fidelity continuous-time sensor model in simulation, making direct #sim2real transfer not possible. By leveraging depth prediction as a pretext task, we pre-train a reactive obstacle avoidance policy with “approximated” simulated events and then fine-tune the perception component with limited events-and-depth real-world data. This technique bridges the sim2real gap for #eventcameras! As at the current state, there is no continuous-time sensor model for event cameras, we hope that this work can finally spur future research leveraging simulation for training event-vision-based policies to create faster, agile robots! Kudos to Anish Bhattacharya, @marcocannic, Vijay Kumar Nikolai Matni UZH Science University of Zurich UZH Space Hub UZH IfI European Research Council (ERC) GRASP Laboratory Penn Engineering

Davide Scaramuzza

17,219 views • 1 year ago

This is ABSOLUTELY SHOCKING & HORRIFYING, if accurate…😳😳😳 According to Alex Jones, a source said that Dan Bongino said that many high ranking officials in the Trump administration are looking to effectively “neutralize” ANY opposition or dissension coming from conservative pundits with large audiences like General Mike Flynn or Steve Bannon etc, and many others. On top of this, they are making ENEMIES LISTS of dissidents who dare to criticize the admin to destroy their lives, and apparently according to this source, Trump himself is totally oblivious to this…Which, in itself is absolutely INSANE, and very hard to believe. The second Trump admin is operating like a ruthless Bolshevik mafioso machine, shutting down any dissidents, who are even on the same side as Trump… I can’t believe I’m saying this, but this is actually WORSE than the Biden admin. Regardless about whatever you think about who or what, this is a HORRIFIC precedent being set, where our government can literally come after anyone because we are using our 1A RIGHTS.

This is ABSOLUTELY SHOCKING & HORRIFYING, if accurate…😳😳😳 According to Alex Jones, a source said that Dan Bongino said that many high ranking officials in the Trump administration are looking to effectively “neutralize” ANY opposition or dissension coming from conservative pundits with large audiences like General Mike Flynn or Steve Bannon etc, and many others. On top of this, they are making ENEMIES LISTS of dissidents who dare to criticize the admin to destroy their lives, and apparently according to this source, Trump himself is totally oblivious to this…Which, in itself is absolutely INSANE, and very hard to believe. The second Trump admin is operating like a ruthless Bolshevik mafioso machine, shutting down any dissidents, who are even on the same side as Trump… I can’t believe I’m saying this, but this is actually WORSE than the Biden admin. Regardless about whatever you think about who or what, this is a HORRIFIC precedent being set, where our government can literally come after anyone because we are using our 1A RIGHTS.

The Patriot Voice

324,614 views • 8 months ago

PFAS, also known as “forever chemicals,” are a large group of synthetic chemicals that break down very slowly over time and are linked to harmful effects on human health. They’re used in a vast array of products, from pots and pans to computers and even dental floss. Laurel Schaider, senior scientist at the Silent Spring Institute in Massachusetts, studies the spread of PFAS chemicals in the drinking water and their effects on human health. She discussed ways that people can take steps to reduce exposure to PFAS in their daily lives. “There are some things that we can do, such as avoiding buying Teflon-coated pans, skipping stain resistant or waterproof items where they're not needed,” she told Horizons host William Brangham. Schaider noted that, while formulations of food packaging have changed, her past advice has been to avoid microwave popcorn and other types of grease-proof food packaging which might contain PFAS. “People are surprised to learn that Glide dental floss is made of Teflon," she said. "There are cosmetics with PFAS." But there is a challenge, Schaider said, because the products don’t include labels that disclose if they contain these chemicals. Horizons from PBS News, dives into the science, health, technology and environmental issues making headlines each week. Visit the PBS News website to watch this week's episode.

PFAS, also known as “forever chemicals,” are a large group of synthetic chemicals that break down very slowly over time and are linked to harmful effects on human health. They’re used in a vast array of products, from pots and pans to computers and even dental floss. Laurel Schaider, senior scientist at the Silent Spring Institute in Massachusetts, studies the spread of PFAS chemicals in the drinking water and their effects on human health. She discussed ways that people can take steps to reduce exposure to PFAS in their daily lives. “There are some things that we can do, such as avoiding buying Teflon-coated pans, skipping stain resistant or waterproof items where they're not needed,” she told Horizons host William Brangham. Schaider noted that, while formulations of food packaging have changed, her past advice has been to avoid microwave popcorn and other types of grease-proof food packaging which might contain PFAS. “People are surprised to learn that Glide dental floss is made of Teflon," she said. "There are cosmetics with PFAS." But there is a challenge, Schaider said, because the products don’t include labels that disclose if they contain these chemicals. Horizons from PBS News, dives into the science, health, technology and environmental issues making headlines each week. Visit the PBS News website to watch this week's episode.

PBS News

17,214 views • 7 months ago

Wind and solar don't work at night or when the wind isn't blowing. Australia is told the solution is batteries! Real world experience shows that batteries are too expensive, too slow to build and don't last long enough to support a grid. During this session with the Australian Renewable Energy Agency (ARENA), I revisited the status of the eight large-scale battery storage projects funded in 2022, noting that $176 million had been allocated but none had completed construction by February. I was told that while all projects are progressing, some face challenges like grid connection issues. I highlighted the significant cost increase from $2.7 billion to $3.1 billion and questioned the efficiency and cost-effectiveness of these batteries compared to coal-fired power stations. I also raised concerns about the stability and reliability of renewable energy sources like solar and wind, and the additional costs associated with making them grid-compatible. Additionally, I asked ARENA about their responsibilities and the financial transparency of their operations. I emphasised the high cost of electricity in Australia compared to countries like China and criticised the impact of net-zero policies on manufacturing. We need to ditch net-zero. Use the cheap resources we have in Australia's ground for Australians first!

Wind and solar don't work at night or when the wind isn't blowing. Australia is told the solution is batteries! Real world experience shows that batteries are too expensive, too slow to build and don't last long enough to support a grid. During this session with the Australian Renewable Energy Agency (ARENA), I revisited the status of the eight large-scale battery storage projects funded in 2022, noting that $176 million had been allocated but none had completed construction by February. I was told that while all projects are progressing, some face challenges like grid connection issues. I highlighted the significant cost increase from $2.7 billion to $3.1 billion and questioned the efficiency and cost-effectiveness of these batteries compared to coal-fired power stations. I also raised concerns about the stability and reliability of renewable energy sources like solar and wind, and the additional costs associated with making them grid-compatible. Additionally, I asked ARENA about their responsibilities and the financial transparency of their operations. I emphasised the high cost of electricity in Australia compared to countries like China and criticised the impact of net-zero policies on manufacturing. We need to ditch net-zero. Use the cheap resources we have in Australia's ground for Australians first!

Malcolm Roberts 🇦🇺

21,336 views • 1 year ago

New short course: Build Long-Context AI Apps with Jamba. Learn about state space models (SSMs), which have emerged as an alternative to transformers! Specifically, Jamba is a hybrid transformer-Mamba architecture that combines strengths of the transformer with ideas from SSMs. This course is built with AI21 Labs and taught by Chen Wang and Chen Almagor. The transformer architecture is computationally expensive when handling very long input contexts. But there's an alternative called Mamba, a selective state space model that can process very long contexts with a much lower computational cost. However, researchers found that the pure Mamba architecture underperforms in understanding the context, and gives lower-quality responses. To overcome this, AI21 developed the Jamba model, which combines Mamba's computational efficiency with the transformer's attention mechanism to help with the output quality. In this course, you’ll learn about how state space models, and Jamba, work. You’ll also learn how to prompt Jamba, use it to process long documents, and build long-context RAG apps. - Learn how Jamba combines transformer and state space model architectures to achieve high performance and quality - Use the AI21 SDK, with an example of prompting over a large 200k-token annual financial report of Nvidia - Use Jamba for tool-calling, with hands-on examples from calling simple arithmetic calculations to a function that returns quarterly company financial reports. - Learn how training for long context is done, and the metrics used for its evaluation - Create a RAG app using the AI21 Conversational RAG tool and build your own RAG pipeline that uses Jamba and LangChain. By the end of this course, you'll learn how to build applications that can handle context as long as an entire book. Please sign up here:

New short course: Build Long-Context AI Apps with Jamba. Learn about state space models (SSMs), which have emerged as an alternative to transformers! Specifically, Jamba is a hybrid transformer-Mamba architecture that combines strengths of the transformer with ideas from SSMs. This course is built with AI21 Labs and taught by Chen Wang and Chen Almagor. The transformer architecture is computationally expensive when handling very long input contexts. But there's an alternative called Mamba, a selective state space model that can process very long contexts with a much lower computational cost. However, researchers found that the pure Mamba architecture underperforms in understanding the context, and gives lower-quality responses. To overcome this, AI21 developed the Jamba model, which combines Mamba's computational efficiency with the transformer's attention mechanism to help with the output quality. In this course, you’ll learn about how state space models, and Jamba, work. You’ll also learn how to prompt Jamba, use it to process long documents, and build long-context RAG apps. - Learn how Jamba combines transformer and state space model architectures to achieve high performance and quality - Use the AI21 SDK, with an example of prompting over a large 200k-token annual financial report of Nvidia - Use Jamba for tool-calling, with hands-on examples from calling simple arithmetic calculations to a function that returns quarterly company financial reports. - Learn how training for long context is done, and the metrics used for its evaluation - Create a RAG app using the AI21 Conversational RAG tool and build your own RAG pipeline that uses Jamba and LangChain. By the end of this course, you'll learn how to build applications that can handle context as long as an entire book. Please sign up here:

Andrew Ng

77,792 views • 1 year ago

VIDEO | As INVS Kaundinya arrives in Muscat, Commodore Prashant C Menon says, "So I am Captain Prashant Menon. I am the officer in charge of the Ocean Sailing Node. So, in this expedition, my responsibility was to identify the crew, select the crew from the large group that maybe had provided for selection. And thereafter, to train them. What do you have to realise that this 1500 year old design. That means today there's nobody living who can teach the team to how to sail. For that matter, even I didn't know how to, train the people. So we undertook various iterations. We selected the team, we sent them to learn carpentry, we sent them to learn riggings, splicing, making these, eyes, and... Everything associated with difficult seamanship activities were there. So, we, the first three months, we, the team was there at the yard, learning from the craftsmen, artisans who have made this deck. Thereafter, we learned how to dock the boat, lifting, the mast can be removed. We removed the mast, got the boat dry-docked, checked the underwater inspection, and thereafter, by September, when monsoon had come down, its intensity had come down. It started affecting us. We did several days at sea sailing the boat and understanding the specifics of a boat of this kind. It is very unique. You see, today's boats have the capability of sailing upwind. Upwind, in the sense, if the wind is coming directly from ahead, of course, you can't take a sailboat right ahead, but you can do a zigzag and having its square mast, it's very different. She needs wind from behind. It's a downwind, so training to sail the boat, turning the direction of the boats, how to hoist, when to hoist, there are two masts. What is the team coordination? All these things were something new to all of us. And we went through this process." #INVSKaundinya

VIDEO | As INVS Kaundinya arrives in Muscat, Commodore Prashant C Menon says, "So I am Captain Prashant Menon. I am the officer in charge of the Ocean Sailing Node. So, in this expedition, my responsibility was to identify the crew, select the crew from the large group that maybe had provided for selection. And thereafter, to train them. What do you have to realise that this 1500 year old design. That means today there's nobody living who can teach the team to how to sail. For that matter, even I didn't know how to, train the people. So we undertook various iterations. We selected the team, we sent them to learn carpentry, we sent them to learn riggings, splicing, making these, eyes, and... Everything associated with difficult seamanship activities were there. So, we, the first three months, we, the team was there at the yard, learning from the craftsmen, artisans who have made this deck. Thereafter, we learned how to dock the boat, lifting, the mast can be removed. We removed the mast, got the boat dry-docked, checked the underwater inspection, and thereafter, by September, when monsoon had come down, its intensity had come down. It started affecting us. We did several days at sea sailing the boat and understanding the specifics of a boat of this kind. It is very unique. You see, today's boats have the capability of sailing upwind. Upwind, in the sense, if the wind is coming directly from ahead, of course, you can't take a sailboat right ahead, but you can do a zigzag and having its square mast, it's very different. She needs wind from behind. It's a downwind, so training to sail the boat, turning the direction of the boats, how to hoist, when to hoist, there are two masts. What is the team coordination? All these things were something new to all of us. And we went through this process." #INVSKaundinya

Press Trust of India

25,632 views • 7 months ago