1. next gen data centers designed from the ground up for AI workloads,
2. first custom silicon for AI training & inference,
3. phase two of Research Supercluster,
4. of the world’s most powerful AI supercomputers.
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Facebook
Reimagining Meta’s infrastructure for the AI age
Meta is executing on an ambitious plan to build the next generation of its infrastructure backbone – specifically for AI. This includes our first custom chip for running AI models, a new AI-optimized data center design, and phase 2 of our 16,000 GPU supercomputer…
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The Hong Kong Monetary Authority announced the commencement of the e-HKD Pilot Programme, including full-fledged payments, programmable payments, offline payments, tokenized deposits, settlement of Web3 transactions and settlement of tokenized assets.
18 companies selected Only Ripple Labs is a company in the field of cryptocurrency, and the others are Alipay Visa Mastercard and 9 banks. Ripple labs is involved in tokenized asset settlement projects.
18 companies selected Only Ripple Labs is a company in the field of cryptocurrency, and the others are Alipay Visa Mastercard and 9 banks. Ripple labs is involved in tokenized asset settlement projects.
Hong Kong Monetary Authority
Hong Kong Monetary Authority - Commencement of the e-HKD Pilot Programme
The Hong Kong Monetary Authority (HKMA) today (18 May) announced the commencement of the e-HKD Pilot Programme. A total of 16 firms (see Annex) from the financial, payment and technology sectors have
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Here are 10 new YC-backed AI companies you need to pay attention to:
1. Stack AI
Focus: Build LLM applications (i.e. ChatGPT) in minutes.
Location: San Francisco, CA.
Website: stack-ai.com
2. Quazel
Focus: Language learning with a conversational AI Tutor.
Location: Zürich, Switzerland.
Website: quazel.com
3. Magicflow
Focus: Webflow for AI development.
Location: Tel Aviv-Yafo, Israel.
Website: magicflow.ai
4. JustPaid io
Focus: AI-powered financial controller automating bill pay and invoicing.
Location: Mountain View, CA.
Website: justpaid.io
5. Linum
Focus: Midjourney for Video.
Location: San Francisco, CA.
Website: linum.ai
6. Layup
Focus: AI that builds workflows across company apps.
Location: San Francisco, CA.
Website: layupai.com
7. Buildt
Focus: AI devtool to search and understand large codebases.
Location: San Francisco, CA.
Website: buildt.ai
8. Type
Focus: The AI-first document editor.
Location: New York, NY.
Website: type.ai
9. Persana AI
Focus: Intelligent sales copilot powered by fine-tuned models.
Location: San Francisco, CA.
Website: persana.ai
10. Turntable
Focus: AI-native operating system for analytics teams.
Location: New York, NY.
Website: turntable.so
1. Stack AI
Focus: Build LLM applications (i.e. ChatGPT) in minutes.
Location: San Francisco, CA.
Website: stack-ai.com
2. Quazel
Focus: Language learning with a conversational AI Tutor.
Location: Zürich, Switzerland.
Website: quazel.com
3. Magicflow
Focus: Webflow for AI development.
Location: Tel Aviv-Yafo, Israel.
Website: magicflow.ai
4. JustPaid io
Focus: AI-powered financial controller automating bill pay and invoicing.
Location: Mountain View, CA.
Website: justpaid.io
5. Linum
Focus: Midjourney for Video.
Location: San Francisco, CA.
Website: linum.ai
6. Layup
Focus: AI that builds workflows across company apps.
Location: San Francisco, CA.
Website: layupai.com
7. Buildt
Focus: AI devtool to search and understand large codebases.
Location: San Francisco, CA.
Website: buildt.ai
8. Type
Focus: The AI-first document editor.
Location: New York, NY.
Website: type.ai
9. Persana AI
Focus: Intelligent sales copilot powered by fine-tuned models.
Location: San Francisco, CA.
Website: persana.ai
10. Turntable
Focus: AI-native operating system for analytics teams.
Location: New York, NY.
Website: turntable.so
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The ChatGPT effect rolls on. Snowflake in advanced talks to buy Neeva as database giant pushes into AI
Database software provider Snowflake has been in advanced talks to acquire Neeva, a search startup founded by former top Google ad tech executive Sridhar Ramaswamy.
Buying Neeva could help Snowflake offer AI software that helps companies search for information in internal documents and data, according to people who do business with Snowflake.
Neeva primarily sells an ad-free web-search app for consumers, but it developed software that combines search with large-language models, which are trained on text to understand the nuances of speech and writing.
That could fit with Snowflake’s efforts to help cloud customers use the kind of AI popularized by chatbots like ChatGPT that respond to conversational commands and can automate some business tasks.
Snowflake is trying to catch up to rivals such as Microsoft’s Azure and Google Cloud that already sell access to such AI software.
Database software provider Snowflake has been in advanced talks to acquire Neeva, a search startup founded by former top Google ad tech executive Sridhar Ramaswamy.
Buying Neeva could help Snowflake offer AI software that helps companies search for information in internal documents and data, according to people who do business with Snowflake.
Neeva primarily sells an ad-free web-search app for consumers, but it developed software that combines search with large-language models, which are trained on text to understand the nuances of speech and writing.
That could fit with Snowflake’s efforts to help cloud customers use the kind of AI popularized by chatbots like ChatGPT that respond to conversational commands and can automate some business tasks.
Snowflake is trying to catch up to rivals such as Microsoft’s Azure and Google Cloud that already sell access to such AI software.
The Information
Snowflake in Talks to Buy Search Startup Neeva in AI Push
Database software provider Snowflake has been in advanced talks to acquire Neeva, a search startup founded by former top Google ad tech executive Sridhar Ramaswamy, according to a person with direct knowledge of the discussions. Buying Neeva could help Snowflake…
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Jeff Bezos' space company has signed a contract with NASA to fly to the moon
NASA has awarded a NextSTEP-2 Appendix P Sustaining Lunar Development (SLD) contract to Blue Origin.
Blue Origin’s National Team partners include Lockheed Martin, Draper, Boeing, Astrobotic, and Honeybee Robotics.
Under this contract, Blue Origin and its National Team partners will develop and fly both a lunar lander that can make a precision landing anywhere on the Moon’s surface and a cislunar transporter.
These vehicles are powered by LOX-LH2. The high-specific impulse of LOX-LH2 provides a dramatic advantage for high-energy deep space missions.
Nevertheless, lower performing but more easily storable propellants (such as hydrazine and nitrogen tetroxide as used on the Apollo lunar landers) have been favored for these missions because of the problematic boil-off of LOX-LH2 during their long mission timelines.
NASA has awarded a NextSTEP-2 Appendix P Sustaining Lunar Development (SLD) contract to Blue Origin.
Blue Origin’s National Team partners include Lockheed Martin, Draper, Boeing, Astrobotic, and Honeybee Robotics.
Under this contract, Blue Origin and its National Team partners will develop and fly both a lunar lander that can make a precision landing anywhere on the Moon’s surface and a cislunar transporter.
These vehicles are powered by LOX-LH2. The high-specific impulse of LOX-LH2 provides a dramatic advantage for high-energy deep space missions.
Nevertheless, lower performing but more easily storable propellants (such as hydrazine and nitrogen tetroxide as used on the Apollo lunar landers) have been favored for these missions because of the problematic boil-off of LOX-LH2 during their long mission timelines.
NASA
NASA Selects Blue Origin as Second Artemis Lunar Lander Provider - NASA
To develop a human landing system for the agency’s Artemis V mission to the Moon, NASA has selected Blue Origin of Kent, Washington. Through Artemis, NASA will explore more of the Moon than ever before, uncovering more scientific discoveries, and preparing…
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Game changes. A central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function.
Here researchers decompose functional MRI signals from pathological and pharmacologically-induced perturbations of consciousness into distributed patterns of structure-function dependence across scales: the harmonic modes of the human structural connectome.
They show that structure-function coupling is a generalisable indicator of consciousness that is under bi-directional neuromodulatory control.
They find increased structure-function coupling across scales during loss of consciousness, whether due to anaesthesia or brain injury, capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness.
The opposite harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure and correlating with physiological and subjective scores.
Overall, connectome harmonic decomposition reveals how neuromodulation and the network architecture of the human connectome jointly shape consciousness and distributed functional activation across scales.
Here researchers decompose functional MRI signals from pathological and pharmacologically-induced perturbations of consciousness into distributed patterns of structure-function dependence across scales: the harmonic modes of the human structural connectome.
They show that structure-function coupling is a generalisable indicator of consciousness that is under bi-directional neuromodulatory control.
They find increased structure-function coupling across scales during loss of consciousness, whether due to anaesthesia or brain injury, capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness.
The opposite harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure and correlating with physiological and subjective scores.
Overall, connectome harmonic decomposition reveals how neuromodulation and the network architecture of the human connectome jointly shape consciousness and distributed functional activation across scales.
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As the deadlock in negotiations to raise the U.S. government's $31.4 trillion debt limit keeps markets tentative, Goldman Sachs warns a potential U.S. debt deal could lead to liquidity strain, causing a ripple effect on Bitcoin
Coindesk
U.S. Debt Deal Could Weigh On Bitcoin Price, Some Say
The Treasury's efforts to build back cash balances after resolution of the debt limit situation might suck out dollar liquidity from system, pushing bitcoin lower.
Microsoft Researchers Introduce Reprompting: An Iterative Sampling Algorithm that Searches for the Chain-of-Thought (CoT) Recipes for a Given Task without Human Intervention.
Paper: arxiv.org/abs/2305.09993
Paper: arxiv.org/abs/2305.09993
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Continuous wearable ultrasound using AI to auto-capture body deep tissue imaging and physiology during mobility for up to 12 hours.
Nature
A fully integrated wearable ultrasound system to monitor deep tissues in moving subjects
Nature Biotechnology - A wearable ultrasound patch monitors subjects in motion using machine learning and wireless electronics.
Hong Kong's Securities Commission: crypto trading to be allowed for retail starting June 1, 2023.
Bloomberg.com
Hong Kong Lets Retail Investors Trade Crypto in New Rules
Hong Kong said retail investors can trade crypto under its new rulebook for the sector, stepping up a drive to develop a digital-asset hub even as the industry and regulators clash elsewhere in Asia.
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Generative approaches to IR that store documents in a transformer model instead of search index, are on the rise.
Though not production ready yet, definitely a trend to watch, with incresingly good results on small collections. Here's some notable papers from this month.
1. How Does Generative Retrieval Scale to Millions of Passages?
Manages scaling to the full MS MARCO collection (8M passages), but results are not near SOTA yet.
arxiv.org/abs/2305.11841
2. Large Language Models are Built-in Autoregressive Search Engines.
Evaluates the capabilities of LLMs to memorize / dream up URL's that actually happen to exist.
arxiv.org/abs/2305.09612
3. TOME: A Two-stage Approach for Model-based Retrieval, by Ruiyang Ren et al.
Uses tokenized URLs as DOCids and also achieves scaling to the full MS MARCO collection with decent results.
arxiv.org/abs/2305.11161
4. Learning to Tokenize for Generative Retrieval.
This paper focuses on the learning of meaningful DOCids using a method called GenRet. New SOTA results of NQ320K, and additional evaluation on MS MARCO, and BEIR.
arxiv.org/abs/2304.04171
5. Recommender Systems with Generative Retrieval.
This paper uses the DSI framework for recommenders, achieves SOTA models on an Amazon dataset and improves retrieval of cold-start items.
arxiv.org/abs/2305.05065
Though not production ready yet, definitely a trend to watch, with incresingly good results on small collections. Here's some notable papers from this month.
1. How Does Generative Retrieval Scale to Millions of Passages?
Manages scaling to the full MS MARCO collection (8M passages), but results are not near SOTA yet.
arxiv.org/abs/2305.11841
2. Large Language Models are Built-in Autoregressive Search Engines.
Evaluates the capabilities of LLMs to memorize / dream up URL's that actually happen to exist.
arxiv.org/abs/2305.09612
3. TOME: A Two-stage Approach for Model-based Retrieval, by Ruiyang Ren et al.
Uses tokenized URLs as DOCids and also achieves scaling to the full MS MARCO collection with decent results.
arxiv.org/abs/2305.11161
4. Learning to Tokenize for Generative Retrieval.
This paper focuses on the learning of meaningful DOCids using a method called GenRet. New SOTA results of NQ320K, and additional evaluation on MS MARCO, and BEIR.
arxiv.org/abs/2304.04171
5. Recommender Systems with Generative Retrieval.
This paper uses the DSI framework for recommenders, achieves SOTA models on an Amazon dataset and improves retrieval of cold-start items.
arxiv.org/abs/2305.05065
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Heading into the era of truly private, personalized AI assistants
Amazing to see LLMs like RedPajama-INCITE 3B run locally on mobile with hardware acceleration using WebAssembly and WebGPU. No need to write custom code for custom hardware.
Amazing to see LLMs like RedPajama-INCITE 3B run locally on mobile with hardware acceleration using WebAssembly and WebGPU. No need to write custom code for custom hardware.
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SO much important stuff being announced Microsoft build today. Much of which is great news for developers and ChatGPT users alike:
1. developers can now use one platform to build plugins that work across both consumer and business surfaces, including ChatGPT, Bing, Dynamics 365 Copilot (in preview) and Microsoft 365 Copilot (in preview).
This is a HUGE win for plugin developers who have adopted early. You can now make your plugin available to orders of magnitude more people without any additional work required.
2. Browsing in ChatGPT!
Microsoft is announcing that Bing is coming to ChatGPT as the default search experience.
This is a huge win, Bing is by many metrics the best game in search, now ChatGPT users will get this out of the box.
Now, answers are grounded by search and web data and include citations so users can learn more, all directly from within chat. The new experience is rolling out to ChatGPT Plus subscribers starting today and will be available to free users soon by simply enabling a plugin.
3. MEGA plugin platform
That's because OpenAI and Microsoft are unifying their plugins standard.
Build once, and you get access to users across:
- ChatGPT
- Bing Chat
- Dynamics 365 Copilot
- Microsoft 365 Copilot
- Windows Copilot
Plugins are a SCREAMING opportunity atm.
1. developers can now use one platform to build plugins that work across both consumer and business surfaces, including ChatGPT, Bing, Dynamics 365 Copilot (in preview) and Microsoft 365 Copilot (in preview).
This is a HUGE win for plugin developers who have adopted early. You can now make your plugin available to orders of magnitude more people without any additional work required.
2. Browsing in ChatGPT!
Microsoft is announcing that Bing is coming to ChatGPT as the default search experience.
This is a huge win, Bing is by many metrics the best game in search, now ChatGPT users will get this out of the box.
Now, answers are grounded by search and web data and include citations so users can learn more, all directly from within chat. The new experience is rolling out to ChatGPT Plus subscribers starting today and will be available to free users soon by simply enabling a plugin.
3. MEGA plugin platform
That's because OpenAI and Microsoft are unifying their plugins standard.
Build once, and you get access to users across:
- ChatGPT
- Bing Chat
- Dynamics 365 Copilot
- Microsoft 365 Copilot
- Windows Copilot
Plugins are a SCREAMING opportunity atm.
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A Japanese robotics company designed a system of six spider-like robotic limbs that the user can fully control
Essentially, turning humans into cyborgs.
Use cases include working in warehouses to hospital surgery rooms.
However, the most significant impact could be improving lives of people with disabilities.
Essentially, turning humans into cyborgs.
Use cases include working in warehouses to hospital surgery rooms.
However, the most significant impact could be improving lives of people with disabilities.
INQUIRER.NET
Jizai Arms: Robot Arm Study Holds Our Cyborg Future
The University of Tokyo took the phrase “lend me a hand” to a new level. Its researchers share robot limbs from their Jizai Arms, a backpack-like system that supports six robotic arms. They spend two days wearing their new arms and swapping with others. Then…
Another milestone in LLM miniaturization.
Scaling up then scale down, will be the rhythm for the open-source AI community.
QLoRA: 4-bit finetuning of LLMs is here! With it comes Guanaco, a chatbot on a single GPU, achieving 99% ChatGPT performance on the Vicuna benchmark:
Paper: arxiv.org/abs/2305.14314
Code+Demo: github.com/artidoro/qlora
Samples
Colab
Scaling up then scale down, will be the rhythm for the open-source AI community.
QLoRA: 4-bit finetuning of LLMs is here! With it comes Guanaco, a chatbot on a single GPU, achieving 99% ChatGPT performance on the Vicuna benchmark:
Paper: arxiv.org/abs/2305.14314
Code+Demo: github.com/artidoro/qlora
Samples
Colab
GitHub
GitHub - artidoro/qlora: QLoRA: Efficient Finetuning of Quantized LLMs
QLoRA: Efficient Finetuning of Quantized LLMs. Contribute to artidoro/qlora development by creating an account on GitHub.
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Figure announces $70M in series A funding. The company is developing a multi-purpose humanoid robot that could one day take on a wide range of tasks traditionally performed by people.
The robots are coming.
The robots are coming.
TechCrunch
Figure raises $70M to build its humanoid robots
I spent a bit of time at Figure’s Sunnyvale offices during a recent visit to the South Bay. The firm is currently in that semi-awkward phase where it’s ready to talk about what it’s working on — but only to a point. That means things like its process and…
The False Promise of Imitating Proprietary LLMs
Open-sourced LLMs are adept at mimicking ChatGPT’s style but not its factuality. There exists a substantial capabilities gap, which requires better base LM.
If you want GPT-4 performance you should use way more than 4 open source language models working together.
One to one you’ll never get the same factuality in particular.
It requires new design patterns as well as better base LMs which will take time & effort
Open-sourced LLMs are adept at mimicking ChatGPT’s style but not its factuality. There exists a substantial capabilities gap, which requires better base LM.
If you want GPT-4 performance you should use way more than 4 open source language models working together.
One to one you’ll never get the same factuality in particular.
It requires new design patterns as well as better base LMs which will take time & effort
Great work from TII in the UAE releasing open source 7b and 40b models as well as a new high quality dataset.
7b https://huggingface.co/tiiuae/falcon-7b
40b https://huggingface.co/tiiuae/falcon-40b
7b https://huggingface.co/tiiuae/falcon-7b
40b https://huggingface.co/tiiuae/falcon-40b
huggingface.co
tiiuae/falcon-7b · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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The Grace Hopper Superchip architecture, shown off by Nvidia's Jensen Huang is super geeky but fascinating.
It basically marries the specialization of the Hopper GPU with the generalization of the Grace CPU by allowing access to all memory.
Here we have a more classic architecture.
Remember that memory cannot be accessed if it cannot be addressed done through a page table. In this traditional approach, GPU & CPU run different page tables.
With a GH Superchip, one page table exists & translates memory addresses so GPU can access CPU memory (here it's LPDDR5X) and CPU can read the GPU's memory (HBM3).
Curious to know how devs will utilize this approach.
It basically marries the specialization of the Hopper GPU with the generalization of the Grace CPU by allowing access to all memory.
Here we have a more classic architecture.
Remember that memory cannot be accessed if it cannot be addressed done through a page table. In this traditional approach, GPU & CPU run different page tables.
With a GH Superchip, one page table exists & translates memory addresses so GPU can access CPU memory (here it's LPDDR5X) and CPU can read the GPU's memory (HBM3).
Curious to know how devs will utilize this approach.