6. Jay Feng - Data science in the startup world

6. Jay Feng - Data science in the startup world

I’ve said it before and I’ll say it again: “data science” is an ambiguous job title. People use the term to refer to data science, data engineering, machine learning engineering and analytics roles, and that’s bad enough. But worse still, being a “data scientist” means completely different things depending on the scale and stage of the company you’re working at. A data scientist at a small startup might have almost nothing in common with a data scientist at a massive enterprise company, for example.

So today, we decided to talk to someone who’s seen data science at both scales. Jay Feng started his career working in analytics and data science at Jobr, which was acquired by Monster.com (which was itself acquired by an even bigger company). Among many other things, his story sheds light on a question that you might not have thought about before: what happens to data scientists when their company gets acquired?

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Jaksot(130)

130. Edouard Harris - New Research: Advanced AI may tend to seek power *by default*

130. Edouard Harris - New Research: Advanced AI may tend to seek power *by default*

Progress in AI has been accelerating dramatically in recent years, and even months. It seems like every other day, there’s a new, previously-believed-to-be-impossible feat of AI that’s achieved by a w...

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129. Amber Teng - Building apps with a new generation of language models

129. Amber Teng - Building apps with a new generation of language models

It’s no secret that a new generation of powerful and highly scaled language models is taking the world by storm. Companies like OpenAI, AI21Labs, and Cohere have built models so versatile that they’re...

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128. David Hirko - AI observability and data as a cybersecurity weakness

128. David Hirko - AI observability and data as a cybersecurity weakness

Imagine you’re a big hedge fund, and you want to go out and buy yourself some data. Data is really valuable for you — it’s literally going to shape your investment decisions and determine your outcome...

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127. Matthew Stewart - The emerging world of ML sensors

127. Matthew Stewart - The emerging world of ML sensors

Today, we live in the era of AI scaling. It seems like everywhere you look people are pushing to make large language models larger, or more multi-modal and leveraging ungodly amounts of processing pow...

21 Syys 202241min

126. JR King - Does the brain run on deep learning?

126. JR King - Does the brain run on deep learning?

Deep learning models — transformers in particular — are defining the cutting edge of AI today. They’re based on an architecture called an artificial neural network, as you probably already know if you...

14 Syys 202255min

125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?

125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?

It’s no secret that the US and China are geopolitical rivals. And it’s also no secret that that rivalry extends into AI — an area both countries consider to be strategically critical. But in a context...

7 Syys 202248min

124. Alex Watson - Synthetic data could change everything

124. Alex Watson - Synthetic data could change everything

There’s a website called thispersondoesnotexist.com. When you visit it, you’re confronted by a high-resolution, photorealistic AI-generated picture of a human face. As the website’s name suggests, the...

18 Touko 202251min

123. Ala Shaabana and Jacob Steeves - AI on the blockchain (it actually might just make sense)

123. Ala Shaabana and Jacob Steeves - AI on the blockchain (it actually might just make sense)

Two ML researchers with world-class pedigrees who decided to build a company that puts AI on the blockchain. Now to most people — myself included — “AI on the blockchain” sounds like a winning entry i...

12 Touko 202254min