正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

the transparency of hyperliquid data is unmatched late night experiment from yesterday, go from any order or liquidation to the wallet analytics behind it in seconds resting orders, stops, take profits, liquidation levels and fills, all clickable data from Hydromancer

José Donato

11,753 subscribers

14,571 次观看 • 4 天前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

hyperliquid l4 book every resting order on its own with the wallet attached. l2 orderbooks only tell you there's size at a level, l4 tells you how many orders, whose, and the sequence 650+ labels resolved from the cryexc public directory data from Hydromancer

hyperliquid l4 book every resting order on its own with the wallet attached. l2 orderbooks only tell you there's size at a level, l4 tells you how many orders, whose, and the sequence 650+ labels resolved from the cryexc public directory data from Hydromancer

José Donato

18,096 次观看 • 3 天前

We built the engine we wished existed. Advanced data analytics, global positioning, pro order types, liquidation alerts, and smart money tracking. All verified and fully audited onchain. Your edge, unleashed from the ground up. Welcome to Hyperdash.

We built the engine we wished existed. Advanced data analytics, global positioning, pro order types, liquidation alerts, and smart money tracking. All verified and fully audited onchain. Your edge, unleashed from the ground up. Welcome to Hyperdash.

Hyperdash

38,358 次观看 • 6 个月前

The worst part of late-night experiments? The data analysis that comes after. OpenBio now automates your analysis - FTIR, spectroscopy data, and more. From data to publication-ready plots and insights in minutes. See it in action:

The worst part of late-night experiments? The data analysis that comes after. OpenBio now automates your analysis - FTIR, spectroscopy data, and more. From data to publication-ready plots and insights in minutes. See it in action:

OpenBio

24,805 次观看 • 9 个月前

What could be the next frontier in data analytics for rugby? How about "off the ball" data? Here is a sample of an animation generated from player GPS data - this was done to investigate defensive connectivity originating from a lineout.

What could be the next frontier in data analytics for rugby? How about "off the ball" data? Here is a sample of an animation generated from player GPS data - this was done to investigate defensive connectivity originating from a lineout.

Simon Chi

124,447 次观看 • 2 年前

Every output is traceable. Computer shows where the data came from and links directly to the source behind key numbers. Click any citation or hyperlinked number to open the underlying SEC filing, earnings transcript, market data page, or licensed source.

Every output is traceable. Computer shows where the data came from and links directly to the source behind key numbers. Click any citation or hyperlinked number to open the underlying SEC filing, earnings transcript, market data page, or licensed source.

Perplexity

48,850 次观看 • 3 个月前

Physical AI is transforming manufacturing, from design to the factory floor. 🦾 Hear how leaders from ABB Robotics, JLR, and Tulip are using AI-powered simulation, synthetic data, and real-time video analytics to unlock new levels of efficiency across the entire product lifecycle. Watch the full video ➡️

Physical AI is transforming manufacturing, from design to the factory floor. 🦾 Hear how leaders from ABB Robotics, JLR, and Tulip are using AI-powered simulation, synthetic data, and real-time video analytics to unlock new levels of efficiency across the entire product lifecycle. Watch the full video ➡️

NVIDIA Omniverse

45,317 次观看 • 4 个月前

ChatGPT connecting to external data sources offers a glimpse into what AI interoperability looks like. Ask any question in ChatGPT and it can now pull data from Box. The future of AI is AI Agents that can access your systems and data to complete any task for you.

ChatGPT connecting to external data sources offers a glimpse into what AI interoperability looks like. Ask any question in ChatGPT and it can now pull data from Box. The future of AI is AI Agents that can access your systems and data to complete any task for you.

Aaron Levie

57,745 次观看 • 1 年前

New configurator, fully built on data binding in Rive - set any values (even from external data), calculate the final price, and test image binding (early access) Currently exploring ways to export all configured data, so it can be integrated wherever you need to receive or store it. Built this with Uliana Kalashnikova, supported the data binding side. Try it:

New configurator, fully built on data binding in Rive - set any values (even from external data), calculate the final price, and test image binding (early access) Currently exploring ways to export all configured data, so it can be integrated wherever you need to receive or store it. Built this with Uliana Kalashnikova, supported the data binding side. Try it:

Daria Nevezhyna

65,172 次观看 • 1 年前

🇺🇸 NVIDIA CEO: PALANTIR TURNS DATA AND HUMAN JUDGMENT INTO INSIGHT “This is Palantir ontology. They take information, they take data, they take human judgment, and they turn it into business insight. We work with Palantir to accelerate everything they do — to process data at a much larger scale and speed, whether it’s structured data from the past or the real-time data shaping the future.” Source: Yahoo Finance

🇺🇸 NVIDIA CEO: PALANTIR TURNS DATA AND HUMAN JUDGMENT INTO INSIGHT “This is Palantir ontology. They take information, they take data, they take human judgment, and they turn it into business insight. We work with Palantir to accelerate everything they do — to process data at a much larger scale and speed, whether it’s structured data from the past or the real-time data shaping the future.” Source: Yahoo Finance

Mario Nawfal

192,979 次观看 • 10 个月前

In an age of instant electronic records, why are we years behind on critical health data? Three years without complete cancer data from the CDC. No real-time updates. No transparency. We have the technology—what we’re missing is institutional accountability.

In an age of instant electronic records, why are we years behind on critical health data? Three years without complete cancer data from the CDC. No real-time updates. No transparency. We have the technology—what we’re missing is institutional accountability.

Mary Talley Bowden MD

54,704 次观看 • 16 天前

Oh wow…Firecrawl just dropped /agent, an API that autonomously navigates and discovers data from any website. You tell it what data you need, it figures out how to find it across complex sites. This is the future of web data.

Oh wow…Firecrawl just dropped /agent, an API that autonomously navigates and discovers data from any website. You tell it what data you need, it figures out how to find it across complex sites. This is the future of web data.

Alvaro Cintas

159,050 次观看 • 8 个月前

President Trump has extracted Indian data from the Prime Minister. The most valuable asset that India has is the data we produce. Any talk about AI has to be based on data, and our 1.4 billion people produce the largest amount on the planet. This includes medical data, data on movement of people, and communication data. All of it has been signed off by PM Modi. And the final thing is that he has promised President Trump that we will buy billions of dollars of imports from the United States every year. : LoP Shri Rahul Gandhi 📍 Keralam

President Trump has extracted Indian data from the Prime Minister. The most valuable asset that India has is the data we produce. Any talk about AI has to be based on data, and our 1.4 billion people produce the largest amount on the planet. This includes medical data, data on movement of people, and communication data. All of it has been signed off by PM Modi. And the final thing is that he has promised President Trump that we will buy billions of dollars of imports from the United States every year. : LoP Shri Rahul Gandhi 📍 Keralam

Congress

13,901 次观看 • 5 个月前

EXCLUSIVE: renowned exposure warnings expert Stephen Petty, whose testing and analysis from East Palestine, Ohio is the most comprehensive, has been under NDA, his data sealed. We got the data. And Petty agreed to speak with us. He says that from the East Palestine testing “between 50 and 70% of the data points…exceeded screening levels…cancer screening levels.” Residents say Petty’s data was HIDDEN from them… instead they were told “The data is nowhere near as bad as we thought it was going to be when this first happened”… so that they would opt in to the class against settlement against Norfolk Southern. Petty: “The argument there’s nothing to see here is factually false. We can’t just walk away from those results. There is a problem there.”

EXCLUSIVE: renowned exposure warnings expert Stephen Petty, whose testing and analysis from East Palestine, Ohio is the most comprehensive, has been under NDA, his data sealed. We got the data. And Petty agreed to speak with us. He says that from the East Palestine testing “between 50 and 70% of the data points…exceeded screening levels…cancer screening levels.” Residents say Petty’s data was HIDDEN from them… instead they were told “The data is nowhere near as bad as we thought it was going to be when this first happened”… so that they would opt in to the class against settlement against Norfolk Southern. Petty: “The argument there’s nothing to see here is factually false. We can’t just walk away from those results. There is a problem there.”

Rich McHugh

10,944 次观看 • 10 天前

Enrollment is now open for the Data Engineering Professional Certificate! Data engineers are the architects of modern organizations, ensuring data is reliable, accessible, and ready for analytics and machine learning. This professional certificate is tailored to equip you with the critical skills, through frameworks and hands-on practice, to excel in this role. Taught by industry expert Joe Reis, co-author of the best-selling book "Fundamentals of Data Engineering," along with 17 guest instructors from the data field, you will gain expertise to start and further your career in the high-demand field of data engineering. Key focus areas: 🗂️ Data Engineering Lifecycle: Learn the important stages of building an efficient data pipeline that creates business value. 📥 Data Ingestion: Learn how to efficiently gather data from various sources. 💾 Data Storage: Master the techniques for storing data securely and cost-effectively. 🔄 Data Transformation: Understand how to clean, organize, and prepare data for analysis and machine learning. 🏗️ Data Architecture Design: Build robust architectures that support scalable, efficient data workflows. 📊 Serving Data: Ensure that data is available to stakeholders when and where they need it to drive business decisions. Enroll now!

Enrollment is now open for the Data Engineering Professional Certificate! Data engineers are the architects of modern organizations, ensuring data is reliable, accessible, and ready for analytics and machine learning. This professional certificate is tailored to equip you with the critical skills, through frameworks and hands-on practice, to excel in this role. Taught by industry expert Joe Reis, co-author of the best-selling book "Fundamentals of Data Engineering," along with 17 guest instructors from the data field, you will gain expertise to start and further your career in the high-demand field of data engineering. Key focus areas: 🗂️ Data Engineering Lifecycle: Learn the important stages of building an efficient data pipeline that creates business value. 📥 Data Ingestion: Learn how to efficiently gather data from various sources. 💾 Data Storage: Master the techniques for storing data securely and cost-effectively. 🔄 Data Transformation: Understand how to clean, organize, and prepare data for analysis and machine learning. 🏗️ Data Architecture Design: Build robust architectures that support scalable, efficient data workflows. 📊 Serving Data: Ensure that data is available to stakeholders when and where they need it to drive business decisions. Enroll now!

DeepLearning.AI

20,833 次观看 • 1 年前

Grok-3 DeepSearch + Gamma : productivity hack 🔥 - Grok-3: DeepSearch is really powerful use it to pull relevant data and people's opinions from X and the internet on any topic. - Gamma : Turn this data into sleek, AI-generated slides in seconds. step-by-step guide 👇

Grok-3 DeepSearch + Gamma : productivity hack 🔥 - Grok-3: DeepSearch is really powerful use it to pull relevant data and people's opinions from X and the internet on any topic. - Gamma : Turn this data into sleek, AI-generated slides in seconds. step-by-step guide 👇

AshutoshShrivastava

1,586,491 次观看 • 1 年前

AI only exists today because it is trained on real data. The better the data input, The better the AI output. We capture incredibly high-quality raw data of real humans, in 3D, from all angles. You do the Math ✍🏻 Our data can vastly improve and expand the capabilities of AI

AI only exists today because it is trained on real data. The better the data input, The better the AI output. We capture incredibly high-quality raw data of real humans, in 3D, from all angles. You do the Math ✍🏻 Our data can vastly improve and expand the capabilities of AI

Metahero.io

24,529 次观看 • 2 年前

The data is in! 🛰️ Science data from NASA's IMAP mission is now available. Its instruments measure the solar wind, the Sun's constant stream of charged particles, and how it shapes our solar system's edge. Explore the data:

The data is in! 🛰️ Science data from NASA's IMAP mission is now available. Its instruments measure the solar wind, the Sun's constant stream of charged particles, and how it shapes our solar system's edge. Explore the data:

NASA Science

28,098 次观看 • 24 天前

David Friedberg: Michael Burry’s Datacenter Math is Wrong “I actually think Michael Burberry's got this wrong.” “What Michael Burry is saying is that all of these hyperscalers have extended their depreciation schedule or the useful life of their data centers by roughly 2x, which cuts the operating costs in half when they report it in earnings. And so it's making their earnings inflate.” “So he's claiming they're cooking the books. Google first made this change in Q1 of 2021, where they said the servers are now going from 3 to 4 years. Separately in 2021, Google took networking equipment from 3 to 5 years. And then in 2023, they took it from 5 to 6 years.” “And so this is a result of this effort where they went in and did an analysis. So what happened?” “What happened in the data centers is that the data centers transitioned from being primarily data storage and data transfer systems, where you would use hard drives and RAM and memory to store data and then transmit it back out, to being data processing centers because of the AI boom.” “So as AI became more important in the data center, more of the dollars that are going into data centers were allocated towards chips from data storage, which initially was hard drives.” “And then suddenly, when you put these processors in to process the data to do AI, the majority of the spend and the majority of the energy is going towards the processors.” “I made some calls and I checked around with some other friends, and everyone says the same thing: that these 7-8 year old TPUs and GPUs that are sitting in the data centers are still being used and they're being used at 100% utilization.” “So that actually justifies and validates the depreciation schedule being much longer versus shorter.”

David Friedberg: Michael Burry’s Datacenter Math is Wrong “I actually think Michael Burberry's got this wrong.” “What Michael Burry is saying is that all of these hyperscalers have extended their depreciation schedule or the useful life of their data centers by roughly 2x, which cuts the operating costs in half when they report it in earnings. And so it's making their earnings inflate.” “So he's claiming they're cooking the books. Google first made this change in Q1 of 2021, where they said the servers are now going from 3 to 4 years. Separately in 2021, Google took networking equipment from 3 to 5 years. And then in 2023, they took it from 5 to 6 years.” “And so this is a result of this effort where they went in and did an analysis. So what happened?” “What happened in the data centers is that the data centers transitioned from being primarily data storage and data transfer systems, where you would use hard drives and RAM and memory to store data and then transmit it back out, to being data processing centers because of the AI boom.” “So as AI became more important in the data center, more of the dollars that are going into data centers were allocated towards chips from data storage, which initially was hard drives.” “And then suddenly, when you put these processors in to process the data to do AI, the majority of the spend and the majority of the energy is going towards the processors.” “I made some calls and I checked around with some other friends, and everyone says the same thing: that these 7-8 year old TPUs and GPUs that are sitting in the data centers are still being used and they're being used at 100% utilization.” “So that actually justifies and validates the depreciation schedule being much longer versus shorter.”

The All-In Podcast

304,297 次观看 • 9 个月前

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

Santiago

142,696 次观看 • 1 年前

New Stage2 PoC payload loader commit fixes the USB Loader and can now goldhen (or any payload/HEN) from payload.bin from USB root or from /data, the USB Loader has now been set to the default loader, this is the end game Offsets file to port to 11.00

New Stage2 PoC payload loader commit fixes the USB Loader and can now goldhen (or any payload/HEN) from payload.bin from USB root or from /data, the USB Loader has now been set to the default loader, this is the end game Offsets file to port to 11.00

LM

78,913 次观看 • 2 年前