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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... show more

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Gabbit Robotics co-founder Nicole Mattero on why the next AI winners won't fight over your screen, they'll fight to get closer to you: She kicks things off with what she admits is a hot take: "My hot take is that hardware is the only moat going forward because anyone's going to be able to spin up a model and make it really good and really cheap." Her logic is simple. Once a strong model is cheap and easy for anyone to build, the model alone can't set you apart. So what actually protects you? "Where does that leave you? Basically companies that have tactile modes such as hardware are the only ones that actually survive." Hardware, though, is only one piece of her argument. The second piece is data: "The models that win in the long run are the ones where private data is their [moat]." From there, Mattero ties the two together. Hardware gives a company one moat. The ability to gather unique personal data gives it another. Put both in place and the edge starts to multiply: "When you have a company that has hardware as a [moat], but then B is able to collect really unique personal data, that also becomes a [moat]." And that, she says, is the reason so many foundation model companies are reaching beyond the screen and into the physical world: "That's why I think a lot of these foundation models are like, let's get something in the home or on the person. It gives them an edge on both fronts."

Gabbit Robotics co-founder Nicole Mattero on why the next AI winners won't fight over your screen, they'll fight to get closer to you: She kicks things off with what she admits is a hot take: "My hot take is that hardware is the only moat going forward because anyone's going to be able to spin up a model and make it really good and really cheap." Her logic is simple. Once a strong model is cheap and easy for anyone to build, the model alone can't set you apart. So what actually protects you? "Where does that leave you? Basically companies that have tactile modes such as hardware are the only ones that actually survive." Hardware, though, is only one piece of her argument. The second piece is data: "The models that win in the long run are the ones where private data is their [moat]." From there, Mattero ties the two together. Hardware gives a company one moat. The ability to gather unique personal data gives it another. Put both in place and the edge starts to multiply: "When you have a company that has hardware as a [moat], but then B is able to collect really unique personal data, that also becomes a [moat]." And that, she says, is the reason so many foundation model companies are reaching beyond the screen and into the physical world: "That's why I think a lot of these foundation models are like, let's get something in the home or on the person. It gives them an edge on both fronts."

Big Brain AI

19,195 views • 1 month ago

We can only trust X 🚨 META/ Facebook planning to build data centers in China, store their data in China, and then GIVE THE CHINESE GOVERNMENT ACCESS to the data “In this document, Facebook is talking about making Chinese user data available to the Chinese government because they're going to store that data in China. Is that correct?” “Correct” “When you store that data in China, Americans who exchange messages or other information with Chinese Facebook users, that would mean the Chinese government could get access to the American data as well, is that correct? “Through the POP servers? Potentially.” “And Facebook was willing to take that risk?” “Yes. There was a lot of discussion about this and ultimately yes.” “I mean, this is, this is extraordinary. This is exactly contrary to what Facebook has represented for years here. They're willing to build data centers, store data in China. They are willing explicitly to give the Chinese government access to it”

We can only trust X 🚨 META/ Facebook planning to build data centers in China, store their data in China, and then GIVE THE CHINESE GOVERNMENT ACCESS to the data “In this document, Facebook is talking about making Chinese user data available to the Chinese government because they're going to store that data in China. Is that correct?” “Correct” “When you store that data in China, Americans who exchange messages or other information with Chinese Facebook users, that would mean the Chinese government could get access to the American data as well, is that correct? “Through the POP servers? Potentially.” “And Facebook was willing to take that risk?” “Yes. There was a lot of discussion about this and ultimately yes.” “I mean, this is, this is extraordinary. This is exactly contrary to what Facebook has represented for years here. They're willing to build data centers, store data in China. They are willing explicitly to give the Chinese government access to it”

Wall Street Apes

80,854 views • 1 year ago

Sam Altman in a new interview says Orbital Data Centers are not going to matter at scale this decade: “I honestly think the idea, with the current landscape of putting data centers in space is ridiculous. If you do the very rough math of launch costs relative to the cost of power on earth and to say nothing how you are going to fix a broken GPU in space— they do break a lot unfortunately— we are not there yet. There will be a time, space is great for a lot of things, Orbital Data Centers are not something that is going to matter at scale this decade.” This clip isn’t going to age well for Sam.

Sam Altman in a new interview says Orbital Data Centers are not going to matter at scale this decade: “I honestly think the idea, with the current landscape of putting data centers in space is ridiculous. If you do the very rough math of launch costs relative to the cost of power on earth and to say nothing how you are going to fix a broken GPU in space— they do break a lot unfortunately— we are not there yet. There will be a time, space is great for a lot of things, Orbital Data Centers are not something that is going to matter at scale this decade.” This clip isn’t going to age well for Sam.

Nic Cruz Patane

72,344 views • 5 months ago

In a world where data is constantly extracted and exploited, CESS is building the decentralized data value infrastructure to take it back. 👊 Web3 starts with ownership—and it starts with your data. In CESS, every storage node is a secure vault. Your data. Your rules. Your future. 🔥 🎥 Watch how CESS is rewriting the future below👇 #CESS #Web3 #Blockchain #Data #DePIN #Crypto #AI

In a world where data is constantly extracted and exploited, CESS is building the decentralized data value infrastructure to take it back. 👊 Web3 starts with ownership—and it starts with your data. In CESS, every storage node is a secure vault. Your data. Your rules. Your future. 🔥 🎥 Watch how CESS is rewriting the future below👇 #CESS #Web3 #Blockchain #Data #DePIN #Crypto #AI

CESS Network

142,631 views • 1 year ago

Lutnick: If you are building a data center, you were going to give power to the grid and drive the energy costs of everybody around that data center lower. Trump is going to bring lower energy prices. Everywhere that a big company builds a big data center, they are going to lower the price of energy in the entire area around it.

Lutnick: If you are building a data center, you were going to give power to the grid and drive the energy costs of everybody around that data center lower. Trump is going to bring lower energy prices. Everywhere that a big company builds a big data center, they are going to lower the price of energy in the entire area around it.

Acyn

494,187 views • 7 months ago

#WATCH | Delhi: On National Statistics Day, Saurabh Garg, Secretary, Ministry of Statistics and Programme Implementation, says, "The theme for National Statistics Day celebration is ' Unlocking the potential of administrative data'. Over the past decade, we have a lot of administrative data, especially because of the growth of Digital India. How we can leverage this administrative data for decision-making is the theme for today's discussions. The PM has been focusing on data-driven decision-making. This is in the context that if we are talking of a Viksit Bharat by 2047, the policies that we take, the decisions that we make, have to be so much more focused and more data-driven. Ministry of Statistics is helping to ensure that the data is more harmonised to make it interoperable."

#WATCH | Delhi: On National Statistics Day, Saurabh Garg, Secretary, Ministry of Statistics and Programme Implementation, says, "The theme for National Statistics Day celebration is ' Unlocking the potential of administrative data'. Over the past decade, we have a lot of administrative data, especially because of the growth of Digital India. How we can leverage this administrative data for decision-making is the theme for today's discussions. The PM has been focusing on data-driven decision-making. This is in the context that if we are talking of a Viksit Bharat by 2047, the policies that we take, the decisions that we make, have to be so much more focused and more data-driven. Ministry of Statistics is helping to ensure that the data is more harmonised to make it interoperable."

ANI

30,758 views • 29 days ago

Did you know that Facebook made $134.9 billion in 2023 from selling your data? Our society has come to the point where we accepted an unfair model in which privacy is being exploited and data gifted to big tech that is selling it for billions. We intend to break the norm of how data is shared on the internet because it is outdated and unfair. You should be empowered with more control and monetization models for your data!

Did you know that Facebook made $134.9 billion in 2023 from selling your data? Our society has come to the point where we accepted an unfair model in which privacy is being exploited and data gifted to big tech that is selling it for billions. We intend to break the norm of how data is shared on the internet because it is outdated and unfair. You should be empowered with more control and monetization models for your data!

Solana ID 🪷

30,451 views • 1 year ago

Marriane Kitany: This bill, the only thing that it is doing is to make sure that the ISPs, when they are selling their data bundles, do not come and give a figure and say I am going to sell you my data bundle for this much for this particular period knowing very well that you will not consume that amount of data by that particular period. This bill has come to take care of the consumer rights #CitizenMondayReport Trevor Ombija, HSC

Marriane Kitany: This bill, the only thing that it is doing is to make sure that the ISPs, when they are selling their data bundles, do not come and give a figure and say I am going to sell you my data bundle for this much for this particular period knowing very well that you will not consume that amount of data by that particular period. This bill has come to take care of the consumer rights #CitizenMondayReport Trevor Ombija, HSC

Citizen TV Kenya

69,641 views • 1 year ago

$Big pharma just handed the AI industry one of the most important reality checks of 2026 (Save this). david friedberg revealed that Anthropic approached major life sciences companies with a pitch, share your proprietary data, sign an NDA and we will give you early access to a specialized life sciences model and nearly every company they spoke with said no. Here is what these pharma companies understood that many enterprises still have not. A large pharmaceutical company may have spent decades and tens of billions of dollars generating proprietary datasets, clinical trial results, genomic sequences, drug interaction data, compound libraries. That data is the business and the competitive moat that separates them from every other player in the industry lives in those datasets. Handing it to an AI lab in exchange for early access to a model is essentially handing your most valuable asset to a company whose entire business model depends on combining your data with everyone else's and then selling the output back to you and to your competitors. Palantir CEO Alex Karp made this exact point that enterprise leaders are paying for AI tokens that generate no tangible business value while simultaneously surrendering their most sensitive operational data to external providers. He called this transferring a company's alpha, the unique advantage that secures the business directly to a third-party lab. Microsoft CEO Satya Nadella echoed the same concern independently, warning that entire sectors might find their accumulated knowledge commoditized if they do not build their own data and model ownership layers. The structural problem is not unique to pharma but it applies to every enterprise sector. Every time an employee runs a query through a third-party frontier model, proprietary workflows, customer data, and strategic processes pass through infrastructure the enterprise does not control. The data already shows the market moving, Open-source captured 67% of all AI tokens processed in the first half of 2026, up from a fraction of that just twelve months earlier. The performance gap between proprietary frontier models and open-source alternatives has nearly closed, DeepSeek costs approximately 1/36th of GPT-5 for comparable workloads. What pharma figured out and what enterprises across every sector are starting to realize is that the model is not the moat but the data is. And once you hand your data to a model company, you have permanently surrendered the asset that took you decades and billions of dollars to build.$

Big pharma just handed the AI industry one of the most important reality checks of 2026 (Save this). david friedberg revealed that Anthropic approached major life sciences companies with a pitch, share your proprietary data, sign an NDA and we will give you early access to a specialized life sciences model and nearly every company they spoke with said no. Here is what these pharma companies understood that many enterprises still have not. A large pharmaceutical company may have spent decades and tens of billions of dollars generating proprietary datasets, clinical trial results, genomic sequences, drug interaction data, compound libraries. That data is the business and the competitive moat that separates them from every other player in the industry lives in those datasets. Handing it to an AI lab in exchange for early access to a model is essentially handing your most valuable asset to a company whose entire business model depends on combining your data with everyone else's and then selling the output back to you and to your competitors. Palantir CEO Alex Karp made this exact point that enterprise leaders are paying for AI tokens that generate no tangible business value while simultaneously surrendering their most sensitive operational data to external providers. He called this transferring a company's alpha, the unique advantage that secures the business directly to a third-party lab. Microsoft CEO Satya Nadella echoed the same concern independently, warning that entire sectors might find their accumulated knowledge commoditized if they do not build their own data and model ownership layers. The structural problem is not unique to pharma but it applies to every enterprise sector. Every time an employee runs a query through a third-party frontier model, proprietary workflows, customer data, and strategic processes pass through infrastructure the enterprise does not control. The data already shows the market moving, Open-source captured 67% of all AI tokens processed in the first half of 2026, up from a fraction of that just twelve months earlier. The performance gap between proprietary frontier models and open-source alternatives has nearly closed, DeepSeek costs approximately 1/36th of GPT-5 for comparable workloads. What pharma figured out and what enterprises across every sector are starting to realize is that the model is not the moat but the data is. And once you hand your data to a model company, you have permanently surrendered the asset that took you decades and billions of dollars to build.

Milk Road AI

16,317 views • 21 days ago

The difference between a Harvard Business School student and a Founder. HBS STUDENT: Lists all the reasons AI Space Compute is hard. FOUNDER: “ I don't disagree with you that building data centers in space is hard. Building data centers in space is extremely hard. . . If you think [demand] is going to double in the next three years - demand for energy from just data centers - and then double in the next three years after that, and then double in the next three years after that, then: We don’t have a choice. We literally have to put data centers in space. So we have to figure this stuff out.” Philip Johnston Starcloud Founders solve problems. Founders KNOW it will be HARD and do it anyway because it simply NEEDS TO BE DONE. That is founder mindset - and that mindset is what Harvard Business School can’t teach.

The difference between a Harvard Business School student and a Founder. HBS STUDENT: Lists all the reasons AI Space Compute is hard. FOUNDER: “ I don't disagree with you that building data centers in space is hard. Building data centers in space is extremely hard. . . If you think [demand] is going to double in the next three years - demand for energy from just data centers - and then double in the next three years after that, and then double in the next three years after that, then: We don’t have a choice. We literally have to put data centers in space. So we have to figure this stuff out.” Philip Johnston Starcloud Founders solve problems. Founders KNOW it will be HARD and do it anyway because it simply NEEDS TO BE DONE. That is founder mindset - and that mindset is what Harvard Business School can’t teach.

Amy

19,909 views • 5 months ago

Chris Cuomo destroys Tom Homan: "I'm not saying this because it's my opinion. I'm saying because all the data is suggestive of this. Your own data, you have the most deaths in '25 and now you're on track to beat it. Is that just a coincidence?"

Chris Cuomo destroys Tom Homan: "I'm not saying this because it's my opinion. I'm saying because all the data is suggestive of this. Your own data, you have the most deaths in '25 and now you're on track to beat it. Is that just a coincidence?"

Aaron Rupar

742,634 views • 2 months ago

Agents will eventually outnumber humans by orders of magnitude. Aaron Levie on the infrastructure that will be needed to manage them: "Whether you think the number is 10x or 100x... we're going to have some order of magnitude more agents than people." "There's going to be just incredibly spectacularly crazy security incidents that will happen with agents, because you'll prompt-inject an agent and find your way through the CRM system and pull out data you shouldn't have access to." "How do you make sure you have the right security, the permissions, the access controls, the data governance?" "We actually don't yet exactly know in many cases how we're going to regulate some of these agents." "No matter what, there's going to need to be a layer that manages the data they have access to and the workflows they're involved in." "This is the new infrastructure opportunity in the era of agents." Aaron Levie on Latent.Space

Agents will eventually outnumber humans by orders of magnitude. Aaron Levie on the infrastructure that will be needed to manage them: "Whether you think the number is 10x or 100x... we're going to have some order of magnitude more agents than people." "There's going to be just incredibly spectacularly crazy security incidents that will happen with agents, because you'll prompt-inject an agent and find your way through the CRM system and pull out data you shouldn't have access to." "How do you make sure you have the right security, the permissions, the access controls, the data governance?" "We actually don't yet exactly know in many cases how we're going to regulate some of these agents." "No matter what, there's going to need to be a layer that manages the data they have access to and the workflows they're involved in." "This is the new infrastructure opportunity in the era of agents." Aaron Levie on Latent.Space

a16z

64,423 views • 4 months ago

There is a new extremely viral theory going around that many of the data centers being built in America aren’t really data centers They’re actually modern day panopticon. A digital surveillance state Even Tucker Carlson thinks this is the case and brings it up with Kevin O'Leary There are some real reasons to question what we’re being told, one of the reasons is the size and scale Think about this China’s largest reported single data center campus is only about 200 football fields in size Compare that to the US where a single data center is being planned at 33,000 football fields. Not to mention there are tons of them that are massive being planned and built It really doesn’t make sense when you compare the population of China being bigger than the US This is a conspiracy, but it’s something to think about because we know America has been moving towards a surveillance state, that’s every real Keep paying attention and questioning things

There is a new extremely viral theory going around that many of the data centers being built in America aren’t really data centers They’re actually modern day panopticon. A digital surveillance state Even Tucker Carlson thinks this is the case and brings it up with Kevin O'Leary There are some real reasons to question what we’re being told, one of the reasons is the size and scale Think about this China’s largest reported single data center campus is only about 200 football fields in size Compare that to the US where a single data center is being planned at 33,000 football fields. Not to mention there are tons of them that are massive being planned and built It really doesn’t make sense when you compare the population of China being bigger than the US This is a conspiracy, but it’s something to think about because we know America has been moving towards a surveillance state, that’s every real Keep paying attention and questioning things

Wall Street Apes

178,337 views • 2 months ago

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 views • 8 months ago

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 views • 1 year ago

Now that Kenyans are more sensitive to data collection, perhaps it's a time to revisit the same issue in CBE. Which is worse because the data is on families and minors. #MaishaKazini

Now that Kenyans are more sensitive to data collection, perhaps it's a time to revisit the same issue in CBE. Which is worse because the data is on families and minors. #MaishaKazini

#LandIsNotProperty Mwalimu Wandia

11,786 views • 1 year ago

Marc Andreessen says AI is hyper democratizing. “Is the future of the world going to be one or a small number of companies, or for that matter, governments or super AIs that kind of own and control everything?” “Or is this a technology that's going to diffuse out and be in everybody's hands?” “This is the time in which AI is actually hyper democratizing. It has spread to more individuals, both in the country and around the world in the shortest period of time of any new technology I think in history.” “The best AIs in the world are in the consumer products.” “This technology is going to be in everybody's hands. And everybody is going to be able to use it to optimize the things that they do, have it be a thought partner, assistant for building companies.” Marc Andreessen 🇺🇸

Marc Andreessen says AI is hyper democratizing. “Is the future of the world going to be one or a small number of companies, or for that matter, governments or super AIs that kind of own and control everything?” “Or is this a technology that's going to diffuse out and be in everybody's hands?” “This is the time in which AI is actually hyper democratizing. It has spread to more individuals, both in the country and around the world in the shortest period of time of any new technology I think in history.” “The best AIs in the world are in the consumer products.” “This technology is going to be in everybody's hands. And everybody is going to be able to use it to optimize the things that they do, have it be a thought partner, assistant for building companies.” Marc Andreessen 🇺🇸

a16z

79,935 views • 8 months ago

So here’s the deal, THE TREASURY DEPARTMENT DATA IS COMPROMISED. Actors without security clearance have been given access to scrape your data. Elon Musk now controls your data and it represents the same level of control exerted by the Chinese government’s social credit system. Musk is now able to profile every name on the treasury data systems. There is no way to sugar coat the fact that your data is no longer secure. It can now be used to target you and not for your benefit, be sure of that. Democrats and advocacy groups can take all the legal action they like, THE DATA IS COMPROMISED and you can’t put the genie back in the bottle. This data can now be used to literally social engineer services to target any perceived enemy of ‘the state’. Call me a conspiracy theorist if you like, but then sit back have a think if any of what I am suggesting is not possible. I analyse big data for a living and I have no solution to this problem and neither does any Democrat telling you it can be fixed.

𝔗𝔯𝔲𝔱𝔥 𝔐𝔞𝔱𝔱𝔢𝔯𝔰

16,366 views • 1 year ago

Dr. John Campbell exposed that the government is HIDING data showing that Covid-19 shots are clearly associated with excess deaths. RUSSELL BRAND: “What … will be the single piece of data that provides a tipping point where the majority of people will say … we were lied to about this?” CAMPBELL: “The obvious one is correlating vaccination status against excess deaths.” “Now, the British government were given the opportunity to release this [data] just last month.” “They actually … said they weren’t going to release it.” “What we don’t know [in the data] is who had the vaccine and did they die?” “The government has REFUSED to release that data.” “We believe that that data has been released to the pharmaceutical industry.” “Bits of data have appeared … in Japan, for example, and also in Italy.” “It doesn’t look good.” “It looks like excess deaths were associated with vaccination.” Russell Brand John Campbell

Children’s Health Defense

25,186 views • 5 months ago