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Talking Big Data and AI w/ Matt Trifiro 

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14 мар 2024

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Комментарии : 14   
@mtrifiro
@mtrifiro 4 месяца назад
09:44 Explaining Reinforcement Learning and Deep Learning Trends 16:24 New AI enables robots to learn novel situations. 21:36 Centralized infrastructure versus dispersed locations. 22:52 Las Vegas adding computer vision to 2000 cameras. 32:16 Distributed data centers are optimal for edge, on-prem and smart city 39:04 Innovation through product evolution and user understanding. 45:34 Marketing industry undergoes digital transformation like manufacturing. 57:10 Understanding complex robotic training for pick-and-pack. 01:03:52 High-speed camera activity requires vast compute power. 01:08:24 Repeated testing exposes biases in tech development. 01:15:31 Redundancy model ensures reliability and uptime. 01:19:39 Zero Gap offers widely avaialbe and city-sc ale AI access network. 01:27:54 Demonstrate AI benefits through seamless infrastructure integration. 01:36:59 Focusing on output or process shapes perception.
@4.0Solutions
@4.0Solutions 4 месяца назад
Thank you for making these time stamps Matt!
@Rafael-vu2xn
@Rafael-vu2xn 4 месяца назад
I love the occasional friction, it creates so much informational value. Thank's for the video!
@4.0Solutions
@4.0Solutions 4 месяца назад
Glad you liked it!
@VastCNC
@VastCNC 4 месяца назад
I think the crux of the trust vs value argument is fundamentally about the hurdle of production grade. A plant floor isn’t going to be generating images of founding fathers, but it’s going to need precision in every function and output
@mtrifiro
@mtrifiro 4 месяца назад
I agree.
@JeffRankinenAmyJoey
@JeffRankinenAmyJoey 4 месяца назад
Preorder now - Walker Reynolds in a box....with off switch and e-stop! Check out 1 hr 26 min 30 sec. Great conversation about the influence of AI in transforming education and "micro" cloud technology. Thanks Walker, Zack Scriven and Matt Trifiro!
@walkerreynolds973
@walkerreynolds973 4 месяца назад
😂
@mtrifiro
@mtrifiro 4 месяца назад
We plan more mischief.
@goldensunalways2228
@goldensunalways2228 4 месяца назад
Nearby data center ?? Shared? Why not have the gpu based server for on premise , a single server ...
@NickNiculita-nicks-software
@NickNiculita-nicks-software 4 месяца назад
because they were talking 2mil a pop
@mtrifiro
@mtrifiro 4 месяца назад
Because then you take on the CAPEX, have to hire the operational expertise, assume tremendous risk that you made the right decision, and you're potentially economically disadvantaged because your competitors can benefit from the economics of shared infrastructure. Every company needs to decide what business they're in. You're probably not in the business of owning and operating your own power generation facility; do you want to be in the business of owning and operating GPUs. What's your core business?
@4.0Solutions
@4.0Solutions 4 месяца назад
Good question. The answer is what the community shared above
@goldensunalways2228
@goldensunalways2228 3 месяца назад
@mtrifiro your argument is valid as long as the company is willing to have shared services that may not be acceptable to some pharma or even sime companies pumping their proprietary data for drug discovery or new product design and even if its willing to accept shared services there needs to be other plants near by to share same services which would become tough for the near by data center providers to provide this till many takers are there together in an industrial cluster. Woukd they serve if there is only one industry asking for nesr by data GPU servers ?
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