Instead, we are going to tap again into a new development in Art and Neural Networks as a metaphor of where AI progress sits today, and what is feasible in the years to come. For our 2019 “initiation” on this topic with foundational concepts, see here. Today, let’s talk about OpenAI’s CLIP model, connecting natural language inputs with image search navigation, and the generative neural art models like VQ-GAN.
Compared to GPT-3, which is really good at generating language, CLIP is really good at associating language with images through adjacent categories, rather than by training on an entire image data set.
Within a decade, the form factor for computing will radically change from staring at screens with flat imagery, to participating in embedded virtual worlds with fully navigable, hyper-realistic environments. Those environments will be filled with software agents, some hybrid human and others entirely AI, that are entirely unrecognizable as anything but real to 90% of the population.
In this conversation, we chat with Kevin Levitt who currently leads global business development for the financial services industry at NVIDIA. He focuses on global trends in accelerated compute and AI for consumer finance – including fintech, retail banking, credit card and insurance. Prior to joining NVIDIA, Kevin served as Vice President of Business Development at Credit Karma, and Vice President of Sales for Roostify.
More specifically, we touch on the role data plays in the financial industry, how the needs of financial institutions have changed, the age of big data, the definitions between artificial intelligence and machine learning, how to train an AI algorithm, the reasoning behind the incredible amount of parameters machine learning solutions consume, the fundamental purpose of AI/ML in financial services, what NVIDIA’s platforms comprise of, and lastly the future of AI/ML.
This week, we look at:
Deep Fakes behind South Park creators' new parody, Sassy Justice
The AI-created author of the fake Hunter Biden intelligence report
GPT-3 winning the love and attention of people on Hacker News
How should we react to these robots and their desire to mess with our minds
Unlike equities, the crypto markets were born from machines, and are constructed from code. Hold dear the tokens in which you believe, and stay away from the stories of easy money. Nothing is easy. To win Russian roulette is not good fortune. It is, instead, a grave mistake to play a lethal game. Have you nothing to lose?
And then Brexit. And then Taiwan and China. And then Covid, again. And then, who knows.
From now on and forever, your counterparty is the data center running an AI cluster on top of the Internet. The data center that has already profiled you and knows everything about you. Bring the tinfoil hat.
This week, we look at a breakthrough artificial intelligence release from OpenAI, called GPT-3. It is powered by a machine learning algorithm called a Transformer Model, and has been trained on 8 years of web-crawled text data across 175 billion parameters. GPT-3 likes to do arithmetic, solve SAT analogy questions, write Harry Potter fan fiction, and code CSS and SQL queries. We anchor the analysis of these development in the changing $8 trillion landscape of our public companies, and the tech cold war with China.