All right, everyone. Welcome to our AI Trends 2023 series. Each year, we invite friends of the show to join us to recap key developments of the year and anticipate future advancement in the most interesting subfields in AI. And today, we’re joined by Samir Singh. Samir is an associate professor in the Department of […]
Good morning, good evening, good night, good wherever you are around the world tuning in to December’s edition of Singularity Net Insiders. It’s wonderful to do this recording for you, it’s fantastic to generally get together and celebrate all our enormous achievements of 2022 with a little look forward to 2023. Thank you as always […]
Hey folks, nice to meet you everyone, both in person and online. My name is Hagai. I lead engineering at MosaicML and I’m going to spend the next 10 minutes or so introducing you to MosaicML Composer and how you can use it to supercharge your PyTorch training. Today, thanks to the amazing AI community […]
Let’s have a quick look at exploratory data analysis for demand forecasting using Plotly. Let’s real quick take a look at the time series demand forecasting data set that we’re going to use. This data set is hosted on Kaggle and I created it. It’s essentially a simulation that looks at forecasting the demand of […]
Hello, I’m Keita Watanabe and if you take a look at the slide, yeah, I actually have my name actually. So, okay, seems like the title, we have two titles but please ignore practice guide on AWS Inferential because in this session I’m not going to talk about Inferential which is already covered in the […]
So my name is Raku Kanti. I’m from IBM Research and today I’ll be talking about how do we scale the PyTorch FSDP on IBM Cloud using Ethernet. So before I jump into how do we use FSDP and what are the key contributions that we have done? What I want to talk about is […]
Welcome to Applications with Deep Narrow Networks with Washington University. In this video I’m going to show you the Kaggle competition that we just competed. This was a Kaggle competition that I put together just all original data for time series forecasting. And we’re going to look at the presentation given by the winning team. […]
Hello folks, I was in New Orleans last week and I had the pleasure of interviewing Laura Ruiz, the primary author on this paper, large language models are not zero-shot communicators. Now this is exploring the ability of language models to perform in clicker check, which I guess from a machine learning audience point of […]
Welcome back to Street Talk, just a little bit of housekeeping before we kick off today. Paulina Salivadove is one of the organizers for a charity AI conference called AI Helps Ukraine. Now, their main goal is to raise funds for Ukraine, both from the folks attending the conference and also from companies sponsoring the […]
It was actually interesting because there were two people to award a team's, Kenrick and Robert Haas. For the first time, so it was a bit of a switch, but that was actually a good thing because they are both very numerical inclined, so to say. And so I could have a good chat with them on the quadratic voting and all that kind of stuff.
The first lecture on GANs was the first lecture of the semester on Generative models. We have seen discriminator models which Model the conditional distribution. Discriminative models find and it aims to find a decision boundary which separates this data from this set of data. So in in in generator models your aim is to just find the distribution of the data and not just to find the boundary.
The Twemal AI podcast is hosted by Sam Charington and Heather Nollis, a principal machine learning engineer at T-Mobile. This week's episode is a look at the work of a machine-learning engineer at the heart of an AI experiment.
GPT-3 was announced nearly two years ago in May 2020. It came out a year after the original GPT paper was published. OpenAI CEO Sam Altman stated a few months ago that GPT4 is on the way.