Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

someone made the most ADDICTIVE game to learn DATA CENTER networking its called Data Center, $6 game, you start with bare floors, buy racks, mount servers, route every cable by hand the INSANE part, every customers traffic shows as colored balls rolling through your cables... you literally see bottlenecks...

1,602,794 Aufrufe • vor 4 Monaten •via X (Twitter)

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 Aufrufe • vor 9 Monaten

Nvidia just spent $4 billion on a technology 99% of people have never heard of. But in 3 years, every AI data center on Earth will need it. And Nvidia just LOCKED UP the supply. Here's what happened: Nvidia invested $2 billion in Coherent and $2 billion in Lumentum. You probably never heard of these companies. They make photonics technology. Systems that transmit data using LIGHT instead of electricity. Sounds like sci-fi. But this is the most important infrastructure bet in AI right now. Here's the problem Nvidia just solved for itself: AI data centers are hitting a wall that has nothing to do with chips, energy, or money... Copper wiring is dying. Every data center on Earth moves data between GPUs using copper cables. But at the speeds AI now demands, copper physically cannot keep up. Signal degrades. Heat explodes. Power consumption skyrockets. Right now, 30% of the electricity in an AI data center is wasted just MOVING data from point A to point B. An MIT researcher said: "Copper's not going to cut it. It gets too hot. Too much power consumption and loss." Jensen Huang admitted it himself too: "We use copper as far as we can, about a meter or two. But where data centers are the size of a stadium, we need something else." That something else is photonics. Replacing copper with laser-powered fiber optics built directly into the chip. The numbers are insane: - 3.5x more power efficient - 10x better network reliability - Data moving at 102 terabits per second Wells Fargo estimates the photonics market will hit $10-12 billion by 2030. And Nvidia just bought privileged access to the two companies that make the advanced lasers every single one of these systems will need. This is the Nvidia playbook on repeat. They did this with CoreWeave. Invested $2 billion, locked up GPU capacity, created a dependent customer. They did this with memory suppliers. Secured HBM allocations years in advance while competitors scrambled. Now they're doing it with photonics. Invest early. Lock up supply. Make the entire ecosystem dependent on companies that are dependent on Nvidia. By the time competitors realize photonics is the bottleneck, Nvidia already OWNS the supply chain. Every data center, AI factory, and GPU cluster will need this technology to function at scale. Nvidia will become even more important.

Ricardo

640,799 Aufrufe • vor 5 Monaten

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

85,012 Aufrufe • vor 1 Jahr

Morgan Stanley just dropped numbers that should make every investor pay attention (Save this). Hyperscalers spent $261B in 2024, they're now projected to spend $1.4T in 2028, a 5x increase in four years and that doesn't even include OpenAI or Anthropic. For the first time, Morgan Stanley is classifying SpaceX as a legitimate hyperscaler alongside Google, Amazon, Microsoft, and Meta. All of it flows into chips, data centers and memory and the supply chain companies sitting beneath the hyperscalers are the ones that will compound quietly. The most underrated play is memory. Micron is the only American HBM supplier, giving it a structural edge in government AI contracts that Samsung and SK Hynix cannot touch. Its entire 2026 HBM4 production is already sold out, revenue nearly tripled to $23.9B, and the memory prices are roughly doubling every year. The cooling problem is one of the most profitable bottlenecks in this entire trade. Vertiv makes the power management, liquid cooling systems and racks that keep GPU clusters from melting and it's up over 100% year to date in 2026 with a $15B+ backlog and guidance raised to $13.5–$14B in full year revenue. Arista Networks (ANET) is the networking infrastructure play, every AI data center needs ultra high speed networking fabric to connect thousands of GPUs together And Arista just doubled its 2026 AI revenue target as the industry shifts from proprietary InfiniBand to Open Ethernet, a shift that plays directly into Arista's strengths. Astera Labs solves the interconnect bottleneck inside data centers, the problem of getting data between chips fast enough to keep up with the GPUs. Revenue grew 93% year over year, it's already profitable, and its customers are Microsoft and Amazon directly. The hyperscalers are the miners and the real money is in the companies selling them the shovels, the electricity, the memory, the cooling, the networking, and the custom silicon. Make sure to follow me Melvin for more underrated infrastructure plays.

Melvin

36,068 Aufrufe • vor 1 Monat

Today in Senate Finance, led by Chair Joan Huffman we dug into the EXPLOSIVE growth of data centers in Texas and per Isaiah Mitchell below... When did this occur? HERE ARE THE FACTS: -335 data centers operating across Texas RIGHT NOW -Texas is #2 in the nation, behind only Virginia -The industry has grown far faster than anyone expected when the exemption was first put in place Data centers got started in Texas in 2013, but the hockey stick hit in 2021 as COVID accelerated the digitization of our entire economy! Remote work made “where you sleep” more important than “where you work,” and demand for data usage at home EXPLODED! Here’s something the public should know: whether it says “AI” on it or not, these data services are already everywhere in Texas. On a recent trip to Florida, every app I used - airlines, hotels, restaurants, gas stations - ran on "the cloud." As Texas Comptroller Chief Revenue Estimator Brad Johnson said: "The cloud is NOT in the atmosphere." Some people may not know this, but we have Phil King to thank, as he authored SB 6 last session, letting Texas lead the way with AI Data Centers! It’s physical: servers and storage in real buildings... That’s why data center physical security matters just as much as cybersecurity. The exemption helped attract this industry. Now the cost to taxpayers has grown into the billions, and it’s our job to take a hard look at whether the benefits still justify the costs! #txlege

Team Bettencourt

25,489 Aufrufe • vor 24 Tagen