Thinking Machines: AI & Philosophy

In this tech talk, we dive deep into the technical specifics around LLM inference.

The big question is: Why are LLMs slow? How can they be faster? And might slow inference affect UX in the next generation of AI-powered software?

We jump into:
  • Is fast model inference the real moat for LLM companies?
  • What are the implications of slow model inference on the future of decentralized and edge model inference?
  • As demand rises, what will the latency/throughput tradeoff look like?
  • What innovations on the horizon might massively speed up model inference?

Creators & Guests

Host
Daniel Reid Cahn
Founder @ Slingshot - AI for all, not just Goliath

What is Thinking Machines: AI & Philosophy?

“Thinking Machines,” hosted by Daniel Reid Cahn, bridges the worlds of artificial intelligence and philosophy - aimed at technical audiences. Episodes explore how AI challenges our understanding of topics like consciousness, free will, and morality, featuring interviews with leading thinkers, AI leaders, founders, machine learning engineers, and philosophers. Daniel guides listeners through the complex landscape of artificial intelligence, questioning its impact on human knowledge, ethics, and the future.

We talk through the big questions that are bubbling through the AI community, covering topics like "Can AI be Creative?" and "Is the Turing Test outdated?", introduce new concepts to our vocabulary like "human washing," and only occasionally agree with each other.

Daniel is a machine learning engineer who misses his time as a philosopher at King's College London. Daniel is the cofounder and CEO of Slingshot AI, building the foundation model for psychology.