We explore Databricks' unusual history, its contributions to the generative AI field for Enterprise, and what its strategies reveal about the evolving landscape of GenAI and data intelligence platforms.
- Starting point of Databricks
- We are open-source and... poor. Changes in strategy that led to $$$
- Turning to Generative AI (and proving again open-source is cool)
- Generative AI's role in the next wave of enterprise data applications
- Product policy: “Cannibalize yourself before someone else does”
- Matei Zaharia, a CTO of Databricks
- Pieter Abbeel Director of the Berkeley Robot Learning Lab, Co-Director of the Berkeley Artificial Intelligence Research (BAIR) lab
- Two talented PhD students: Hao Liu, Wilson Yan
Since the bloom of social media, it’s been tough times for journalism as so many voices appeared and the cacophony was deafening.
AI-generated content adds even more infotrash. But surprisingly enough, I think that AI is here to bring us back to the quality of journalism, both as a risk factor and as an enabler.
Today, we have something special prepared just for you: a 6-month report (from January 2023 to early July 2023) detailing the transformative impact that the launch of ChatGPT has had in China, India, and the UK.
How should we refer to AI applications like chatbots? He/she/it/they?
We often use human-like language to describe AI. And there is a word for it: anthropomorphism in AI.
The media is ignoring the very real issue of anthropomorphism in AI. But it has serious consequences.
How do you refer to AI chatbots or other technologies? Do you give them nicknames?
We also write about LLMs! https://www.turingpost.com/t/FMOps