Top 3 trends to watch out for in Deep Tech, according to fellow 4 European investors who spoke at Frontier DeepTech:

πŸ‘‡
πŸ‘©β€πŸ’» New Algorithms

"We have only just started to scratch the surface of what we can do with data and new algorithms" - according to @mickhalsband from Lunar Ventures
πŸ›°οΈ Space infrastructure

"Space and space-related technologies can help humans evolve over the next 20-50 years and beyond" - according to Avantika Gupta from Type One Ventures
βš›οΈ Nuclear Fusion

"The possibility of endless clean energy on earth is definitely worth investing in" - according to Liliya Chechel from @Shell Ventures
Bonus sectors:

Amelia Armour from @AmadeusCapital was the one asking the question, but I'm pretty sure she'll be looking for companies in Health, AI and Semiconductor. In the semi space, Amadeus already backed UK champions like Simon Thomas from Paragraf

#deeptech
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More from @francesco_srv

Oct 14
"Nothing we are doing online is basically safe."

I think this quote from @zama_fhe 's founder @randhindi yesterday can sum up the 1st day of @f_deeptech

#cybersecurity was a recurring theme throughout the 1st day in a way:
It was mentioned during the #quantumcomputing panel I chaired yesterday, where I was joined by ORCA Computing's Richard Murray , @QuantinuumQC 's Waseem Shiraz and @aegiq_tech 's Max Sich

It was of course the key theme of Rand's talk on homomorphic encryption
And it came back right at the end when Roderick Rodenburg snatched victory of the startup competition for @RosemanLabs - awarder by the 3 VC judges: Obinna Nnewuihe, @SpaceSaxena and @qualleja
Read 6 tweets
Oct 12
Physics is about to be eating the world.

Software is finishing up the appetiser, before the the main course arrives.

Happy for you all to quote me on this one 10 years from now.

If one day my VC ever gets to the levels of @a16z - this would probably be the reason.
Their founder's "software is eating the wold" classic quote underpinned their "contrarian" investment thesis at a time when the world was recovering from the dot-com crash.
They were right and the VC world today sees them as one of the legends alongside the early Silicon Valley pioneers still around, like @sequoia

Today they think the future is the metaverse. I.e. digital-2.0

I don't.

That's my contrarian view.
Read 14 tweets
Oct 9
What I learned from this week​: most startup investors forget the 1st VC principle ─the Power Law.

Especially the "outsider money".

Outsider money is growing in the industry and peaked in 2021.

Now it seems to have come down, somewhat, but it's still going strong.
Outsider capital is pretty much any investor who is not a VC or has not been a professional angel for 5 years or more. Most high net worths and Family Office investors fall into this category (but not all!)
Having money to invest + Knowing what it takes to build a business β‰  being able to generate high returns.

The missing piece is superior access to deals.

At least having access to some of the KEY deals.

It may seem silly.

Startup founders need money. Investors have money.
Read 8 tweets
Oct 7
To all my fellow Europeans who moan about big tech regulations all the time. Sometimes it's actually GOOD. And the US is copying it.
The US is crawling closer to passing the Journalism Competition and Protection Act: which would allow publishers to bargain with Meta and Google and force them to pay for news.

Similar legislation is being discussed in the EU and in particular in France.
But the real pioneer was Australia, where early sign of success (i.e. redistribution of some revenue back to newspapers and reversing the industry downfall) is bringing back new life to real news scouts, rather than fake-news prone internet media platforms.
Read 6 tweets
Oct 6
Is it just me or the made up title "serial entrepreneur" mostly attracts HNWs and repels VCs?

Logic:

πŸ‘‡
Assumption 1) unsophisticated rich people trying their hand with venture may love the idea of a "safe bet" and quick returns.
Assumption 2) VC mechanics really requires them to hunt for outlier dragon returners (that normally take 5-10 years to exit) and the 1-3X quick exits are what happens when startups fail to get THERE... but at least get SOMEWHERE
Read 5 tweets
Oct 4
Did you know that a machine learning model trained without human labels can predict physics even when information is lacking?

I was geeking around to discover examples of self-supervised learning (i.e. not using labelled data for AI training) on recurrent neural networks.

Why? Image
Because if you think about it, the brain is full of feedback connections.

Training a recurrent neural net (i.e. a system with loops) is not always easy (feedback tends to blow up stuff like when microphones and speakers feed back on each other).
Especially if you want to do away with a controlled environment to train the model with.

But since biology often taught us how to build better machine learning models, you can argue there is probably potential in exploring such systems.
Read 7 tweets

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