pranade

Congrats Paras – amazing story!

Great question. The CPG data landscape is a fragmented mess. We're actually tackling this at arena (https://arena-ai.com) to build out AI foundation models for the industry. We have some tips and potentially tools that might be useful to you. Would be great to get your input / hear your pain points if you're up for it

Nice work!

This kid is awesome

The subluminal application is particularly interesting, because it seems almost feasible. Is there a practical path to meeting these mass/energy requirements though?

Love the design -- pretty cool work!

Arena | Lead Machine Learning Scientist + Deep Learning Scientist | Full-time | Remote / NYC — We founded Arena a little over a year ago, to bring advanced ML techniques out of the lab (lots of active learning, for instance), and apply them at scale, for large enterprises where we can measurably prove impact. We're profitable, with multiple large scale Fortune 500 customers in pilots & in production.

There are 8 of us on the team, almost entirely technical – a mix of Machine Learning Engineers and Scientists with deep academic background and experience. The team includes 3 former founders. Co-founder and CEO founded Kimono Labs (YC W14, acquired by Palantir).

Competitive compensation, with material equity ownership for the right fit. — Apply by sending us an email: careers@arena-ai.com | https://arena-ai.com

Interesting, thanks for putting this together. Curious – have you found good sources of granular data for credit card spending and movement patterns, perhaps from traffic/ride-sharing/mobile (that's anonymous/protects user privacy ofc)?

Thanks for flagging this. Working on a fix now!

Great references -- thanks!

Thanks for the feedback. 100% agree, we will make that bolder and bigger so it's super clear

Arena | Active learning AI for pricing | NYC | https://arena-ai.com/

Hiring 1 Machine Learning Scientist & 1 Front-end engineer. Founded by YC alum (Kimono W14). Team = 5 people. Founded 1 year ago. Profitable. Hyper-linear growth.

Email us at careers@arena-ai.com

Today we are focused on pricing. We built a simulator that models hyper-specific market conditions and competitive dynamics to allow human users and AI agents to predict what will happen if they change the price of a product.

Pricing is just the start. We plan to create simulated, virtual copies of many more real environments - with the ultimate purpose of training a broader set of reinforcement learning agents for different tasks.

Arena | Active learning AI for Pricing | NYC | Full-time | https://arena-ai.com/

Hiring 1 Machine Learning Scientist & 1 Front-End engineer. Founded by YC alum (Kimono W14). Team = 5 ppl. Founded < 1 year ago. Profitable. Hyper-linear growth.

Email us at careers@arena-ai.com

Today, we are focused on pricing. We built a simulator that models hyper-specific market conditions and competitor dynamics to allow human users and AI agents to predict what will happen if they change the price of a product.

Pricing is just the start. We plan to create simulated, virtual copies of many more parts of the physical world – with the ultimate purpose of training a broader set of reinforcement learning agents for different tasks.

Super interesting article. Curious, with the pharmaceutical developments we have already, what would be an upper bound for human AQ today? How might we measure it?

Interesting. Are there plans to make any of this available online, e.g., Coursera?

Awesome!

Awesome stuff, guys!

Yes, in fact we built API in partnership with EDGAR-online. It uses EDGAR-Online data but makes it available in a manner that's easier to digest and consume.

Super helpful analysis, both from an employer perspective and for the employee -- we need more transparency on this

awesome

Great work!

This is awesome!

Yes - totally agree!

Yes, definitely can't draw a trend based on 2 data points, but the difference is still quite interesting. Also, with kimono you can extend and expand the analysis with new APIs to tease out more interesting trends.

Good point - thanks for the feedback! Yes, it's been about 75% on the R16 games. It's also fully interactive - so you can change the weights to explore relationships with historical data that might be interesting.

Thanks for catching - for now you'll have to view it in Chrome.

Yes, that is with high certainty, but not 100%. We'll fix the messaging hear - thanks for flagging. Also, it's interactive so you can change the weights and see what happens

Feel free to build apps on top of the API - we'd love to see you build something cool with it.

Not sure I understand the point... ? The reason for correlating against price is in hope of finding a leading indicator to movement so that you can better understand the relationship between bitcoin price and some other metric. This would in theory help you ultimatly make better returns by better predicting when to buy or sell...

Exactly. gotta read the fine print :) We think this could get more interesting with time though. It was really cool when we got our first couple days of data and were able to see the basic principles of economics at work by looking at the anti-correlation of supply with price!