Robohub.org
 

“Deep learning is the most fundamental advance in AI research since AI started in 1956”


by
14 July 2016



share this:
Screenshot from presentation about deep learning we may use everyday. Source: Frank Chen, with Andreessen Horowitz

Screenshot from presentation about deep learning we may use everyday. Source: Frank Chen, with Andreessen Horowitz

Frank Chen, a partner at Andreessen Horowitz, the Silicon Valley venture capital and private equity firm, said, “It is absolutely non-controversial that deep learning is the most fundamental advance in AI research since the start [of A.I.] in 1956.”

In the 45-minute podcast primer shown below – a worthwhile investment of your time – he went on to say:

“We [Andreessen Horowitz] think AI and deep learning can be a fundamental and technology platform shift as mobile and cloud have been in the last 5-10 years … All the serious applications from here on out need to have deep learning and AI inside in exactly the same way that all serious computing systems needed to have Intel chips inside of them. I think now about the startups that we see, that deep learning needs to be inside these new systems as a fundamental technique that we expect to see in all serious applications moving forward.”

Enjoy. It’s an informative primer.



tags: ,


Frank Tobe is the owner and publisher of The Robot Report, and is also a panel member for Robohub's Robotics by Invitation series.
Frank Tobe is the owner and publisher of The Robot Report, and is also a panel member for Robohub's Robotics by Invitation series.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Robot Talk Episode 167 – Automating construction, with Jan Petrš

  23 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Jan Petrš from École Polytechnique Fédérale de Lausanne about novel robot designs for construction and architecture.

ACM SIGAI Autonomous Agents Award 2027 open for nominations

  20 Oct 2026
Nominations are solicited for the 2027 ACM SIGAI Autonomous Agents Research Award.

Powered by muscle cells, a paper-thin robot swims through watery maze

  19 Oct 2026
MIT engineers’ new aquabot offers a way to design small, efficient “biohybrid” robots.

Robot Talk Episode 166 – Evolving robot bodies and brains, with Rika Antonova

  16 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Rika Antonova from the University of Cambridge about using artificial intelligence to develop complimentary robot hardware and algorithms.

Humanoid robots can sprint and box – but the real test is doing the laundry

  12 Oct 2026
No robot system can yet reliably handle the whole laundry process. Even folding remains a challenge.

Robot Talk Episode 165 – Robots behind the research, with Kushant Patel

  09 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Kushant Patel from Brookhaven National Laboratory about robots that work in scientific facilities, such as particle accelerators.

What three days building a robot taught me

and   07 Oct 2026
The brief sounded simple: build a small autonomous robot, then make it survive increasingly difficult mazes. Simple... right? Until you actually have to build one.


↑


AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence