SingularityNET: Inside SingularityNET | December 2022

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 […]

Exploratory Data Analysis (EDA) with Plotly for Timeseries Demand Forecasting

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 […]

Top Kaggle Solution for Fall 2022 Semester

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. […]

#82 – Dr. JOSCHA BACH – Digital Physics, DL and Consciousness [UNPLUGGED]

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 […]

SingularityNET: Deep Funding | Community Governance – November 9, 2022

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.

11-785, Fall 22 Lecture 23: Generative Adversarial Networks (Part 1)

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.

Engineering Production NLP Systems at T-Mobile

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.