Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Very special Training Data drops today: Making Cities Awesome ☺️ We haven’t featured an application company on Training Data in a while. The diffusion of AI is the Most Important Thing, and the highest-stakes application category of all is the one sitting near the base of Maslow’s hierarchy: safety....

sonyatweetybird's profile picture

Sonya Huang 🐥

30,501 subscribers

34,092 Aufrufe • vor 1 Monat •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

4 Kommentare

Profilbild von Sonya Huang 🐥
Sonya Huang 🐥vor 1 Monat

Listen to the full episode: Apple: Spotify: YouTube:

Profilbild von Jonathan Sandhu
Jonathan Sandhuvor 1 Monat

What exactly becomes better for a city besides the pitch deck?

Profilbild von Dave Mellish
Dave Mellishvor 1 Monat

It’s becoming extremely difficult not to focus on 🐥’s taste in fashion, and the confidence with which she pulls it off. Pay attention kids. S-tier.

Profilbild von Sonya Huang 🐥
Sonya Huang 🐥vor 1 Monat

ha!! merci ☺️

Ähnliche Videos

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.”
1:33

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

304,450 Aufrufe • vor 11 Monaten

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.
0:43

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

Aaron Levie

17,543 Aufrufe • vor 6 Monaten

every question in this clip is an ownership question, especially data because when everyone has access to the same intelligence, the only input that separates your business from the next one is the data you own your data is decades of decisions, customers, mistakes, and edge cases that exist nowhere else on earth that is the moat and enterprises are waking up to the fact that they've been leaking it one api call at a time my prediction is this: data ownership is going to absolutely matter in the world we're going into and whoever's building the infrastructure for it is going to have a very good decade.
0:48

every question in this clip is an ownership question, especially data because when everyone has access to the same intelligence, the only input that separates your business from the next one is the data you own your data is decades of decisions, customers, mistakes, and edge cases that exist nowhere else on earth that is the moat and enterprises are waking up to the fact that they've been leaking it one api call at a time my prediction is this: data ownership is going to absolutely matter in the world we're going into and whoever's building the infrastructure for it is going to have a very good decade.

Adeniyi.sui

13,834 Aufrufe • vor 3 Monaten

We need the data centers. We have to win the AI race. My guest for episode 5 of Counterweight is Manhattan Institute's Judge Glock. This spring he wrote about Loudoun County, VA in City Journal. Loudoun, one of the richest counties in America, with a median household income of around $170,000, has become the unlikely center of a new data center-based industrial revolution. And it's not just Loudoun. Data center construction is up about twenty times nationwide in three years, leading to an enormous political backlash. New York State imposed a moratorium on data center construction, and even Republican Greg Abbott of Texas has put a temporary pause in place. Meanwhile, speaking for myself, I’ve seen a ton of fear-mongering about them, with very little in the way of clear explanation of what the costs and benefits are and what they mean for the localities that might bring them in. I've brought Judge on to walk through in granular detail how data centers work, how Loudoun County became ground zero for the data center boom, and the recent pushback against data centers. We also talk about the unfortunate habit that AI CEOs have of seeming like the gloomiest people in the world in relation to the products they are trying to sell.
40:20

We need the data centers. We have to win the AI race. My guest for episode 5 of Counterweight is Manhattan Institute's Judge Glock. This spring he wrote about Loudoun County, VA in City Journal. Loudoun, one of the richest counties in America, with a median household income of around $170,000, has become the unlikely center of a new data center-based industrial revolution. And it's not just Loudoun. Data center construction is up about twenty times nationwide in three years, leading to an enormous political backlash. New York State imposed a moratorium on data center construction, and even Republican Greg Abbott of Texas has put a temporary pause in place. Meanwhile, speaking for myself, I’ve seen a ton of fear-mongering about them, with very little in the way of clear explanation of what the costs and benefits are and what they mean for the localities that might bring them in. I've brought Judge on to walk through in granular detail how data centers work, how Loudoun County became ground zero for the data center boom, and the recent pushback against data centers. We also talk about the unfortunate habit that AI CEOs have of seeming like the gloomiest people in the world in relation to the products they are trying to sell.

Will Chamberlain

21,345 Aufrufe • vor 1 Monat

Hot topic in vogue is what happens to systems of record in an era of 1000x more agents than humans. Aaron Levie has been the CEO of Box for 20 years and believes that systems of record become more important, not less, with agents: “Systems of record were built for a TAM of human employees. And that was sort of where the value maxed out at. And now maybe we'll have a hundred times more agents than people or a thousand times more agents than people. So I think on a relative basis, the agent layer will seize growth from zero to a trillion. But the system of record layer now has a thousand times more users on it that need to access data and need to execute a workflow and need to move things through various events. And importantly, you need as an enterprise to care about data integrity and security and the controls in your workflow and traffic copying the agents. So basically, this is where I am very diametrically opposed to the view that the system of record gets is squeezed into a database interaction layer because you actually need all of the core system of record properties for the agents to operate on.”
2:15

Hot topic in vogue is what happens to systems of record in an era of 1000x more agents than humans. Aaron Levie has been the CEO of Box for 20 years and believes that systems of record become more important, not less, with agents: “Systems of record were built for a TAM of human employees. And that was sort of where the value maxed out at. And now maybe we'll have a hundred times more agents than people or a thousand times more agents than people. So I think on a relative basis, the agent layer will seize growth from zero to a trillion. But the system of record layer now has a thousand times more users on it that need to access data and need to execute a workflow and need to move things through various events. And importantly, you need as an enterprise to care about data integrity and security and the controls in your workflow and traffic copying the agents. So basically, this is where I am very diametrically opposed to the view that the system of record gets is squeezed into a database interaction layer because you actually need all of the core system of record properties for the agents to operate on.”

Corinne Marie Riley

119,410 Aufrufe • vor 10 Monaten

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado
1:49

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado

a16z

80,437 Aufrufe • vor 3 Monaten

.Aaron Levie says AI agents may take years to diffuse from engineering into the rest of knowledge work. "The models are really good at code, and the work is verifiable." "You have 5 or 10 things that make agents work in an enterprise context for engineering." "The users are less technical, the data is much more fragmented, the systems are much more legacy." "That's why it's going to be a number of years for this diffusion to roll from what we're seeing in Silicon Valley, into the rest of knowledge work."
1:27

.Aaron Levie says AI agents may take years to diffuse from engineering into the rest of knowledge work. "The models are really good at code, and the work is verifiable." "You have 5 or 10 things that make agents work in an enterprise context for engineering." "The users are less technical, the data is much more fragmented, the systems are much more legacy." "That's why it's going to be a number of years for this diffusion to roll from what we're seeing in Silicon Valley, into the rest of knowledge work."

MTS

13,046 Aufrufe • vor 6 Monaten

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.
1:21

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 Aufrufe • vor 1 Jahr

You REALLY NEED to LISTEN 🎧 to Robin Hillier on… CANADA'S REAL POVERTY LINE! Using the most accurate data analysis available l'Il demonstrate the actual poverty line for what is considered one of the most affordable and best cities in the country to live in $26/he after tax. I ran these calculations myself and through a professional research grade Al and two other extremely powerful Al's using the household metric which has the lowest percentage of error They are dead on and that is the poverty line for one of the best cities in the entire country. #liberal #conservitive
4:07

You REALLY NEED to LISTEN 🎧 to Robin Hillier on… CANADA'S REAL POVERTY LINE! Using the most accurate data analysis available l'Il demonstrate the actual poverty line for what is considered one of the most affordable and best cities in the country to live in $26/he after tax. I ran these calculations myself and through a professional research grade Al and two other extremely powerful Al's using the household metric which has the lowest percentage of error They are dead on and that is the poverty line for one of the best cities in the entire country. #liberal #conservitive

JayGen 𝕏 er🇨🇦

19,315 Aufrufe • vor 11 Monaten

AI agents should add to the systems your client already uses. One client spent several years and $10 million on one ERP migration. Offer that client a move to an AI-native CRM, and "you've lost them." So we build our agents inside the systems of record. They read the data in Salesforce and do the work in Salesforce. When a human must be in the loop, the agent sends a message in Slack. The staff need no new training, so they use the agents faster. SMB clients with no CRM are the exception. You can put them on one. If you want to work as a forward deployed engineer, build on what your client already uses.
2:29

AI agents should add to the systems your client already uses. One client spent several years and $10 million on one ERP migration. Offer that client a move to an AI-native CRM, and "you've lost them." So we build our agents inside the systems of record. They read the data in Salesforce and do the work in Salesforce. When a human must be in the loop, the agent sends a message in Slack. The staff need no new training, so they use the agents faster. SMB clients with no CRM are the exception. You can put them on one. If you want to work as a forward deployed engineer, build on what your client already uses.

The Startup Ideas Podcast (SIP) 🧃

15,996 Aufrufe • vor 24 Tagen

🚨 PhD Statistician Dr. Regina Watteel Exposes How Trudeau Used Fraudulent Data to Lockdown the Unvaccinated "The Freedom Convoy came in and it put a lot of pressure on the provinces to relent on their passports and on the federal government to end their mandates and travel restrictions. So out of desperation...Trudeau's government imposed the Emergencies Act...to stop the momentum...but they needed to do more. They needed the science...When you look at our data it showed that the COVID cases were dominated by the vaccinated...So Trudeau was in desperate need of science in justification for his mandates. So in comes Fisman and his colleagues and what Fisman does, is he and his colleagues concoct a model to simulate fake data that shows the opposite of what real data shows. Fake data that shows its the unvaccinated that have higher COVID-19 rates...They used this fake results to scapegoat the unvaccinated...and the media ran with it." Regina Watteel Natali Morris
8:30

🚨 PhD Statistician Dr. Regina Watteel Exposes How Trudeau Used Fraudulent Data to Lockdown the Unvaccinated "The Freedom Convoy came in and it put a lot of pressure on the provinces to relent on their passports and on the federal government to end their mandates and travel restrictions. So out of desperation...Trudeau's government imposed the Emergencies Act...to stop the momentum...but they needed to do more. They needed the science...When you look at our data it showed that the COVID cases were dominated by the vaccinated...So Trudeau was in desperate need of science in justification for his mandates. So in comes Fisman and his colleagues and what Fisman does, is he and his colleagues concoct a model to simulate fake data that shows the opposite of what real data shows. Fake data that shows its the unvaccinated that have higher COVID-19 rates...They used this fake results to scapegoat the unvaccinated...and the media ran with it." Regina Watteel Natali Morris

Chief Nerd

242,186 Aufrufe • vor 2 Jahren

Chris Camillo explains how Bloom Energy is solving AI data center energy usage problems… “ $BE is one of the only companies in the world that has a method to essentially bring almost an infinite amount of energy to these data centers." And we won't get into all the technology, but they are now working with hyperscalers and they are a resource for energy that will allow a data center to get ramped up quicker. "So, even though it costs a little bit more money today to put an energy cell from Bloom, an energy box from Bloom, which are energy cells, it essentially takes things like natural gas, but instead of burning the natural gas, there is a chemical process that turns that natural gas into energy for the data center."
1:27

Chris Camillo explains how Bloom Energy is solving AI data center energy usage problems… “ $BE is one of the only companies in the world that has a method to essentially bring almost an infinite amount of energy to these data centers." And we won't get into all the technology, but they are now working with hyperscalers and they are a resource for energy that will allow a data center to get ramped up quicker. "So, even though it costs a little bit more money today to put an energy cell from Bloom, an energy box from Bloom, which are energy cells, it essentially takes things like natural gas, but instead of burning the natural gas, there is a chemical process that turns that natural gas into energy for the data center."

The Iced Coffee Hour

277,703 Aufrufe • vor 5 Monaten

The stakes around data are changing. As artificial intelligence moves into everything, the demands on our data compound. So do the risks. We now share our ideas, intentions, and reasoning with these systems. The skills and experience that we’ve spent a lifetime building. For institutions and builders, it’s their competitive intelligence, their proprietary insights. The edge that separates winners from everyone else. Data is our most valuable asset. This is also a moment of massive opportunity. Agentic AI has the potential to create new abundance for humanity. But for that future to be possible, agents need data that makes them capable. Data they control, that moves with them across applications, and that they can independently verify. As owners, we’ll need to prove to regulators what our agents did. All things that today’s infrastructure cannot provide. Sui represents the first half of the solution. A coordination layer built for the machine economy. Walrus is the data platform that completes it. Walrus makes data a first-class asset. The terms of access and monetization stay with its owner, not a vendor. It empowers builders to ship agents and apps without locking themselves or their customers into any model or platform. Users carry their data, their memory, and their work across systems while cryptographic proof replaces vendor trust. Everything is anchored on Sui: a coordination layer and a data layer built to move as one. Welcome to the new era of Walrus. The data platform built for the demands of AI.
0:56

The stakes around data are changing. As artificial intelligence moves into everything, the demands on our data compound. So do the risks. We now share our ideas, intentions, and reasoning with these systems. The skills and experience that we’ve spent a lifetime building. For institutions and builders, it’s their competitive intelligence, their proprietary insights. The edge that separates winners from everyone else. Data is our most valuable asset. This is also a moment of massive opportunity. Agentic AI has the potential to create new abundance for humanity. But for that future to be possible, agents need data that makes them capable. Data they control, that moves with them across applications, and that they can independently verify. As owners, we’ll need to prove to regulators what our agents did. All things that today’s infrastructure cannot provide. Sui represents the first half of the solution. A coordination layer built for the machine economy. Walrus is the data platform that completes it. Walrus makes data a first-class asset. The terms of access and monetization stay with its owner, not a vendor. It empowers builders to ship agents and apps without locking themselves or their customers into any model or platform. Users carry their data, their memory, and their work across systems while cryptographic proof replaces vendor trust. Everything is anchored on Sui: a coordination layer and a data layer built to move as one. Welcome to the new era of Walrus. The data platform built for the demands of AI.

Walrus

20,335 Aufrufe • vor 22 Tagen

I don't think people understand that one of the biggest real-world use cases for Crypto it is happening - right now. FedEx, just sat down with Mance Harmon of $HBAR and explained why they chose Hedera to track millions of packages a day, to 220 countries. Dale Christie, Blockchain Strategist at FedEx said in 2018, FedEx tried building its own blockchain... But it wouldn’t scale so they chose Hedera. Why? Every package generates hundreds - sometimes thousands - of data points, and Hedera enables the key facts to move through customs at the speed of data, not paper. “When you are a trusted shipper and I am a trusted receiver… that data can move through customs at the speed of data and keep it moving.” One of the largest logistics companies in the world just publicly said Hedera is the foundation they’re building on. Hedera is the most undervalued token imo. and this is one of the biggest use cases Crypto's ever seen.
16:29

I don't think people understand that one of the biggest real-world use cases for Crypto it is happening - right now. FedEx, just sat down with Mance Harmon of $HBAR and explained why they chose Hedera to track millions of packages a day, to 220 countries. Dale Christie, Blockchain Strategist at FedEx said in 2018, FedEx tried building its own blockchain... But it wouldn’t scale so they chose Hedera. Why? Every package generates hundreds - sometimes thousands - of data points, and Hedera enables the key facts to move through customs at the speed of data, not paper. “When you are a trusted shipper and I am a trusted receiver… that data can move through customs at the speed of data and keep it moving.” One of the largest logistics companies in the world just publicly said Hedera is the foundation they’re building on. Hedera is the most undervalued token imo. and this is one of the biggest use cases Crypto's ever seen.

Mark

44,717 Aufrufe • vor 8 Monaten

In the second episode of Scenius Studio's mini-series "The Use-Case", I sit down with Andrej Co-Founder of touch grass. Grass gives users the ability to earn ownership in the Grass network by supplying the protocol with their unused internet bandwidth for data scraping purposes (something that is already happening to most of us and we don’t get paid!). The grass protocol packages this scraped web data and sells it to AI companies who have insufficient data to further develop their models. With over 3 millions users and millions of annualized revenue, Grass is a real commercial business with a roadmap that makes it one of the most exciting projects at the intersection of crypto x AI and data. In this episode we discuss: ➔ Andrej’s background in physics, finance, and sports betting ➔ Big companies using your IP address without your knowledge or permission ➔ How the Grass protocol puts a toll booth on your internet bandwidth highway ➔ Packaging web scraped data and selling it to AI companies building Multi-Modal models ➔ Dynamics between the Grass Protocol and the labs entity developing Grass’ IP ➔ Protocol design decisions to ensure that all tokenholders (VCs, team, and community) are aligned ➔ Why Grass needed to be built on crypto rails to maximize its potential ➔ The future of LLMs and how they will search for context and information Hope you enjoy this episode of Scenius Studio's "The Use-Case". Links to listen in bio or below👇
1:12

In the second episode of Scenius Studio's mini-series "The Use-Case", I sit down with Andrej Co-Founder of touch grass. Grass gives users the ability to earn ownership in the Grass network by supplying the protocol with their unused internet bandwidth for data scraping purposes (something that is already happening to most of us and we don’t get paid!). The grass protocol packages this scraped web data and sells it to AI companies who have insufficient data to further develop their models. With over 3 millions users and millions of annualized revenue, Grass is a real commercial business with a roadmap that makes it one of the most exciting projects at the intersection of crypto x AI and data. In this episode we discuss: ➔ Andrej’s background in physics, finance, and sports betting ➔ Big companies using your IP address without your knowledge or permission ➔ How the Grass protocol puts a toll booth on your internet bandwidth highway ➔ Packaging web scraped data and selling it to AI companies building Multi-Modal models ➔ Dynamics between the Grass Protocol and the labs entity developing Grass’ IP ➔ Protocol design decisions to ensure that all tokenholders (VCs, team, and community) are aligned ➔ Why Grass needed to be built on crypto rails to maximize its potential ➔ The future of LLMs and how they will search for context and information Hope you enjoy this episode of Scenius Studio's "The Use-Case". Links to listen in bio or below👇

Ben Jacobs

22,468 Aufrufe • vor 1 Jahr

Today I called for a hearing on the Four Pillars strategy to address public drug use, addiction, and overdoses in San Francisco Prevention, harm reduction, enforcement, and treatment. Zurich deployed this model and now it is one of the safest cities *in the world.*
1:49

Today I called for a hearing on the Four Pillars strategy to address public drug use, addiction, and overdoses in San Francisco Prevention, harm reduction, enforcement, and treatment. Zurich deployed this model and now it is one of the safest cities *in the world.*

Jackie Fielder

184,177 Aufrufe • vor 1 Jahr

I got a smart meter recently and saw you can download a HDF file with the data so I had the idea of writing a script that could parse that and show the data in a useful manner. However I discovered that someone has already done this and done a really good job on it. The video explains how it works. In simple terms it uses the ESB smart meter data and shows a breakdown of how much data you are using and when and also recommends plans and estimates what each one would cost based on the data. The tool is available at easier to read on Laptop or Tablet or then your phone to Landscape.
1:26

I got a smart meter recently and saw you can download a HDF file with the data so I had the idea of writing a script that could parse that and show the data in a useful manner. However I discovered that someone has already done this and done a really good job on it. The video explains how it works. In simple terms it uses the ESB smart meter data and shows a breakdown of how much data you are using and when and also recommends plans and estimates what each one would cost based on the data. The tool is available at easier to read on Laptop or Tablet or then your phone to Landscape.

Carlow Weather

298,565 Aufrufe • vor 2 Jahren

Maajid Nawaz from Italy on the Pope's encyclical address warning about Ai: “Peter Thiel’s Palantir as a company, using the UK as a case study, already has, due to Prime Minister Keir Starmer, already has contracts to manage the nation’s, all of the nation’s health data unified on one platform and that health data being interpreted as it is by Palantir’s autonomous AI, making life and death decisions on the nation’s health. Palatir also separately has a contract with the Metropolitan Police using a combination of not just facial recognition but predictive programming to determine crime and to set the police’s priorities. This is something that, they already have this deal with the Metropolitan Police, but in addition, if you add Palantir’s contracts with the Ministry of Defence in the UK, like it has in the Department of Defence in the United States of America, you can see how a combination of health data, domestic crime surveillance and foreign war-mongering, being all under the auspices of one private company called Palantir, in the UK and in the US, it’s the same, it is a particularly worrying scenario.”
1:12

Maajid Nawaz from Italy on the Pope's encyclical address warning about Ai: “Peter Thiel’s Palantir as a company, using the UK as a case study, already has, due to Prime Minister Keir Starmer, already has contracts to manage the nation’s, all of the nation’s health data unified on one platform and that health data being interpreted as it is by Palantir’s autonomous AI, making life and death decisions on the nation’s health. Palatir also separately has a contract with the Metropolitan Police using a combination of not just facial recognition but predictive programming to determine crime and to set the police’s priorities. This is something that, they already have this deal with the Metropolitan Police, but in addition, if you add Palantir’s contracts with the Ministry of Defence in the UK, like it has in the Department of Defence in the United States of America, you can see how a combination of health data, domestic crime surveillance and foreign war-mongering, being all under the auspices of one private company called Palantir, in the UK and in the US, it’s the same, it is a particularly worrying scenario.”

أبو عمّار

24,409 Aufrufe • vor 5 Monaten

“Spain is one of the safest countries in the world.” “Is it thanks to surveillance?” “No.” “The UK has much more surveillance.” “Is it a safer country?” “No.” Carissa Véliz just slammed the argument that surveillance leads to safety. And she called the rise of surveillance technology a “symptom of authoritarianism.” “Let’s suppose that we do have more data, and we can better track people, and better… predict people’s behavior.” “Is that a good thing?” “If you want an authoritarian regime, that’s a great thing.” “If you want a liberal democracy that is healthy, in which people feel… freedom to protest anonymously and peacefully, then no, that’s not a good thing at all.” Carissa Véliz
1:47

“Spain is one of the safest countries in the world.” “Is it thanks to surveillance?” “No.” “The UK has much more surveillance.” “Is it a safer country?” “No.” Carissa Véliz just slammed the argument that surveillance leads to safety. And she called the rise of surveillance technology a “symptom of authoritarianism.” “Let’s suppose that we do have more data, and we can better track people, and better… predict people’s behavior.” “Is that a good thing?” “If you want an authoritarian regime, that’s a great thing.” “If you want a liberal democracy that is healthy, in which people feel… freedom to protest anonymously and peacefully, then no, that’s not a good thing at all.” Carissa Véliz

Jan Jekielek

19,966 Aufrufe • vor 2 Monaten

Handshake AI CSO Sahil Bhaiwala reveals how they build simulated white-collar work environments to train frontier AI agents: "An environment consists of a few elements. The first is the software tools the agent needs access to. If I'm an investment banker, I have access to Excel, SEC EDGAR where all the financial reports are, and PowerPoint. Agents need the same access." "We build simulated versions because of infrastructure and access constraints. Labs are querying that tool thousands of times in a given second." "The second thing you need is data that populates the environment. If I'm building a financial model, I need the data room with the messy files from the company I'm evaluating." "The final piece is tasks and verifiers. What are the requests of the agent that would reflect what a real investment banker might ask. We try to find tasks complex and realistic enough that the models fail. If the model can't perform, we know it needs more training data." "What we send to labs is essentially a Docker file, a full containerized task. It has the tools the model has access to, the full data that populates the world, and the task and verifier. We'll send tens of thousands of these to a given lab for just one domain." Handshake Garrett Lord
3:53

Handshake AI CSO Sahil Bhaiwala reveals how they build simulated white-collar work environments to train frontier AI agents: "An environment consists of a few elements. The first is the software tools the agent needs access to. If I'm an investment banker, I have access to Excel, SEC EDGAR where all the financial reports are, and PowerPoint. Agents need the same access." "We build simulated versions because of infrastructure and access constraints. Labs are querying that tool thousands of times in a given second." "The second thing you need is data that populates the environment. If I'm building a financial model, I need the data room with the messy files from the company I'm evaluating." "The final piece is tasks and verifiers. What are the requests of the agent that would reflect what a real investment banker might ask. We try to find tasks complex and realistic enough that the models fail. If the model can't perform, we know it needs more training data." "What we send to labs is essentially a Docker file, a full containerized task. It has the tools the model has access to, the full data that populates the world, and the task and verifier. We'll send tens of thousands of these to a given lab for just one domain." Handshake Garrett Lord

MTS

17,292 Aufrufe • vor 2 Monaten