Sweet and Simple, right from the basics. Loved it !

Wonderful session, next level is see how to have the data available to general public for a productive use via blockchain technology (hopefully possible)

Excellent examples and descriptions of the major concepts being used today. Thank you.

Thank you for your time Mr. Ramey, it helped us understand AI better 

ML & DL

This is Esmeralda at Gaytimes 2023, redux. The 90 minute set I would have played before Babylon fell and the gay set times were cut short.

Let me set the scene. It's Saturday night. Half past send it o'clock. You roll into Muriel's club space, hot and steaming. The room is so full people are climbing in the windows.

What follows is an assortment of big house bangers, tech house and silly rave tunes from the 90s-00s. And a couple of special favourites. Speed dealer sunnies are recommended at the 28 minute mark.

There's a lot of new territory for me here in terms of material, technique, the physical and emotional investment in the mix. And my first time playing at a festival. Whipping that room into a hot mess was really fun, would do again.

Gaytimes 2023

Scopic Records - a new UK label which aims to "bring newcomers and artists with backgrounds, regardless of their background or gender" - launches with a single by its founder New Digital Fidelity in collaboration with singer Monet. We get three nicely different mixes of 'Getting Colder' in all. The A-side is taken up by the club mix, a classic New York deep house groove with chunky pianos chords and Monet's confident vocal performance. The flip begins with the original, a slower version but still effortlessly groovy, bringing its soul, jazz, and R&B influences to the fore. US techno's man of the moment Byron the Aquarius completes the set by turning the track inside out with shuffling hats, snapping machinefunk snares and a bubbling bass, making it even more impressive by exposing its moving parts and giving them a neat polish.

A1.New Digital Fidelity-Gettin Colder feat Monet (Club Mix)

Gunnar Underground – Remember

Label/Cat#: Yellhouse Records – YHR-2
Country: Sweden
Year: 1999
Genre: Electronic
Style: House
Format: Vinyl, 12", 33 ⅓ RPM

Tracklist
A – Remember (Let The Good Time (Piano) Rollmix)
B – Remember (Original Mix)

More information: http://www.discogs.com/Gunnar-Underground-Remember/release/2437

Gunnar Underground - Remember (Original Mix) (1999)

“Father Fader” gets remixed by top french producer Alan.D for a classic tech house remix of the original's bluesy gospel detroit inspired classic. We use the term "tech house" carefully, as nowadays it translates a bland funkless universe of same sounding generic tracks that chart Beatport with anonimity and absense of creativity... We are using the term as it was used in the 90's, as the remix sounds like something out on Paper Recordings or Pagan. It sounds like classic Soma tracks and remixes by Maas or I:Cube. An elegant version, perfect for massive floors!!

The original has a Housier feel: a few smartly picked sampled vocal bits and smart key chops looped into a very raw analog sounding beat, while a heart racing narrative evolves around the stacking of stabs and organs that keep building on an ever increasing galvanizing tension. Peak time, fast paced deep winner.

Label: @PercebesMusica
Original Track: @LarryQuest
Remixer: @DJ-AlanD

Entrega

PREMIERE: Larry Quest - Father Fader (Alan.D Remix) [Percebes Música]

Second hour - DJ Rody guestmix

1. Bario Jazz Gang - Linda Cancao 
2. Borka and The Gang - L.O.V.E
3. Borka and The Gang - Free Your Soul
4. Motorcitysoul - Potelea
5. Chanknous - Magnesio (Toni Lionni Rmx)
6. Dam Swindle - Just Not Norma
7. Casbah feat Osundlade - Lets Invade To Amazon (Yoruba Soul Rmx)
8. Soul Wun , St. Germain - Thank You
9. Retromigration - Versace Sheet
10. Solar House - Magic In The City (Keri Chandler Rmx)
11. Ross Couch - Last One Home
12. Shaka - When The Sun Goes Down 
13. Montreaux - Trut Comitee

RadioB - DeepBox live: Sanny + DJ Rody (Leep Deep) / 18.9.2023

Download

A1.JesusGonsev - Terminal5

"Machine learning is to big data as human learning is to life experience," says Christopher Nguyen, the co-founder and CEO of big data intelligence company Adatao. Sure, but then, what IS big data? (especially as it's become a buzzword that captures so many things)... 

On this episode of the a16z Podcast, Nguyen puts on his former computer science professor hat to describe 'big data' in relation to 'machine learning' -- as well as what comes next with 'deep learning'. Finally, the former Google exec shares how Hadoop and Spark evolved from the efforts of companies dealing with massive amounts of real-time information; what we need to make machine learning a property of every application (why would we even want to?); and how we can make all this intelligence accessible to everyone.

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The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.
 
This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

a16z Podcast: Making Sense of Big Data, Machine Learning, and Deep Learning

Turkish Airlines Boarding Music - Landing

Think of our inaugural episode of The AI Podcast as a guide for the perplexed.  Host Michael Copeland speaks with NVIDIA's Will Ramey about the history behind today's AI boom and the key concepts you need to know to get your head around a technology that's reshaping the world.

Ep. 1: Deep Learning 101 - Will Ramey, NVIDIA Senior Manager for GPU Computing

Bryan Catanzaro, vice president for applied deep learning research at NVIDIA, talks about how we know an AI technology is working, the potential for AI-powered speech, and where we’ll see the next deep learning breakthroughs.

Ep. 2: Where Deep Learning Goes Next - Bryan Catanzaro, NVIDIA Applied Deep Learning Research

When you have “a really hot, frothy space” like AI, even the most basic questions — like what is it good for, how do you make sure your data is in shape, and so on — aren’t answered. This is just as true for the companies eager to adopt the technology and get into the space, as it is for those building companies around that space, observes Joe Spisak, Head of Partnerships at Amazon Web Services. “People treat it like magic,” adds a16z general partner Martin Casado.

This magical realism is especially true of AI, because by definition — i.e., machines learning — there is a bit of a “black box” between what you put in and what you get out of it. Which may be fine… Except when you have to completely change the data being fed into that black box, or you’re shooting for a completely different target to come out of it. That’s why, observes Scott Clark, CEO and co-founder of SigOpt, “an untuned, sophisticated system will underperform a tuned simple system” almost every time.

So what does this mean for organizations going from so-called “toy” problems in R&D to real business results tied to KPIs and ROI? In this episode of the a16z Podcast, Casado, Clark, and Spisak (in conversation with Sonal Chokshi) share their thoughts on what’s happening and what’s needed for AI in practice, given their vantage points working with both large companies and AI startups. What does it mean for data scientists and domain experts? For differentiation and advantage? Because even though we finally have widely available building blocks for AI, we need the scaffolding too… and only then can we build something powerful on top of it.

a16z Podcast: AI, from 'Toy' Problems to Practical Application

Sama in Konya (Sufi Music)
Recording by Jean During
Published by Mahoor Institute of Culture and Art

Gazel : Kani Karaca / Segah Pesrev : Yusuf Pasa

One person, one interview, one story. Join us as we explore the impact of AI on our world, one amazing person at a time -- from the wildlife biologist tracking endangered rhinos across the savannah here on Earth to astrophysicists analyzing 10 billion-year-old starlight in distant galaxies to the Walmart data scientist grappling with the hundreds of millions of parameters lurking in the retailer’s supply chain. Every two weeks, we’ll bring you another tale, another 25-minute interview, as we build a real-time oral history of AI that’s already garnered nearly 3.4 million listens and been acclaimed as one of the best AI and machine learning podcasts. Listen in and get inspired.

https://blogs.nvidia.com/ai-podcast/

Ep. 1: Deep Learning 101 - Will Ramey, NVIDIA Senior Manager for GPU Computing

The AI Podcast

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