Crypto holds the key to quantum resilience, yet this is often overlooked. At @plcapital we've made several bets in the space (denoted by an *) particularly around FHE. We consider FHE a bet on quantum resilience 🧵
Today we are announcing our $1B Series C, but money isn’t the story. The story is what we’ll do with it, and the scale of the challenge ahead.
Our mission isn’t constrained by capital, supply, or demand. It’s constrained by talent. To build America’s next great power company, we need the engineers, operators, and creatives ready to take on the challenge to join us.
Power is the most important product in the world. It runs through everything: our homes, hospitals, schools, factories, and future. And the grid that delivers it is breaking.
At Base, we’re building the future of power so human progress can accelerate. In the past two years, we’ve grown from an idea into one of the fastest growing energy companies in America.
Now we’re entering a new phase of growth. Our first manufacturing site is rising in the heart of Austin, inside the former Austin American-Statesman printing press. Here we’ll build our own hardware to meet surging demand and scale nationwide. This is a key step in putting a battery on every home in the country.
Few teams get to say their work powers human progress. We do. With a billion dollars of fuel, our next wave of growth will be defined not by capital, but by people who choose to step up, take ownership, and build the next great American power company.
The old system is breaking. Come build the new one.
Our Series C was led by Addition, with participation from both new and existing investors including Trust Ventures, Valor Equity Partners, Thrive Capital, Lightspeed, Andreessen Horowitz, Altimeter, StepStone, Elad Gil, 137 Ventures, Terrain, Waybury, Ribbit, CapitalG, Spark, BOND, Lowercarbon, Avenir, Glade Brook, Positive Sum, and 1789.
Who I should follow for a balanced take on the “reasoning” capabilities of LLMs?
Hard to separate opinions from facts...
I did a bit of tinkering with LLMs to do deductive vs. inductive reasoning and it’s not inspiring confidence on the “deductive” part
@emiyazono
@emiyazono A few of the better resources I found in this last week:
Prof. Thomas Dietterich: https://t.co/95pagw3fEU
Francois Chollet: https://t.co/Dgrivn252d
Inductive or Deductive reasoning of LLMs: https://t.co/ehIum4iVVx
@Richard86864523@fchollet One of the key unlocks are efficiency enhancements (e.g. prompt caching and GPT4o-mini), which have reduced costs to a point where this is becoming economically viable.
A good thought experiment to think through what other use cases are becoming viable with this lower cost
@Richard86864523 and I spun up an experiment on reproducing bugs by evolving the output of LLMS.
This was inspired by @fchollet's thinking that evolutionary algorithms can extend LLM capabilities to novel tasks
summary here: https://t.co/JLdvsjKvvf