Here's a Strudel fork that uses LLMs to turn instructions like "add a bass layer" into code: https://github.com/stuhlmueller/strudel-llm
241 karma · joined March 14, 2013
Elicit is the leading AI research assistant. We automate high-quality reasoning so that humanity makes more breakthroughs in every domain: from climate change to the gut microbiome to longevity and economic policy.
We’ve scaled to over 200,000 monthly users by word of mouth and just crossed $1MM in annual revenue, 5 months after launching subscriptions.
We’re now building out the core software engineering team.
Ought is using large language models to build Elicit, an AI-powered research assistant that automates and extends parts of the scientific research process. We are part startup, part research lab, and we're dedicated to making tools which help people think.
The ideal candidate has several years experience working on infrastructure: e.g. production and test environments, ML model management, data pipelines, CI/CD, Kubernetes, GitOps, etc.
Apply here: https://ought.org/careers/
If you're not sure if it's a good fit, email me to check (andreas@ought.org).
Ought is using large language models to build Elicit, an AI-powered research assistant that automates and extends parts of the scientific research process. We are part startup, part research lab, and we're dedicated to making tools which help people think.
Apply here:
- Full-stack Software Engineer: https://ought.org/careers/software-engineer
- Machine Learning Research Engineer (NLP): https://ought.org/careers/ml-engineer
If you're not sure if it's a good fit, email me to check (andreas@ought.org).
For now we've chosen to build Elicit around aggregating and synthesizing research - what is the evidence in each paper, what are the arguments, how do they come together to inform questions people care about?
We think research is a good starting point for figuring out how to use language models to do high-quality reasoning because (a) researchers care a lot about what's true and (b) research is already more structured than most other sources of knowledge.
You can also teach Elicit to do custom tasks by giving input-output examples of intended behavior, e.g. for brainstorming counterarguments or decomposing research questions.
Our mailing list at list.elicit.org has more about what we've recently been adding.
(I work on Elicit, the tool used in the thread.)
We're a non-profit AI research lab. Our goal is to make machine learning solve tasks where success can’t be reduced to a simple metric. We're working towards a future where ML is as helpful for open-ended questions like “Should I get this medical procedure?” and “What career is right for me” as it is for optimizing ad click-through rates.
To do this, we build systems that decompose thinking about hard questions into small subtasks, some of which can be automated. We then compositionally build complex thoughts out of these simple pieces. Humboldt talked about natural language as a system that "makes infinite use of finite means" -- an infinite number of sentences can be created using a finite number of grammatical rules. At Ought, we work on mechanisms that have similar flexible compositionality.
We'll pay a $5,000 referral bonus to whoever refers the person we end up hiring for our team lead role (careers@ought.org, terms: https://bit.ly/2lw3Q8w). Our benefits and compensation package are at market with similar roles in the Bay Area.
Apply here:
- Software Engineer: https://ought.org/careers/software-engineer
- Engineering Team Lead: https://ought.org/careers/engineering-lead
We're a non-profit AI research lab. Our goal is to make machine learning solve tasks where success can’t be reduced to a simple metric. We're working towards a future where ML is as helpful for open-ended questions like “Should I get this medical procedure?” and “What career is right for me” as it is for optimizing ad click-through rates.
To do this, we build systems that decompose thinking about hard questions into small subtasks, some of which can be automated. We then compositionally build complex thoughts out of these simple pieces. Humboldt talked about natural language as a system that "makes infinite use of finite means" -- an infinite number of sentences can be created using a finite number of grammatical rules. At Ought, we work on mechanisms that have similar flexible compositionality.
We'll pay a $5,000 referral bonus to whoever refers the person we end up hiring for our team lead role (careers@ought.org, terms: https://bit.ly/2lw3Q8w). Our benefits and compensation package are at market with similar roles in the Bay Area.
Apply here:
- Software Engineer: https://ought.org/careers/software-engineer
- Engineering Team Lead: https://ought.org/careers/engineering-lead
We're a non-profit AI research lab. Our goal is to make machine learning solve tasks where success can’t be reduced to a simple metric. We're working towards a future where ML is as helpful for open-ended questions like “Should I get this medical procedure?” and “What career is right for me” as it is for optimizing ad click-through rates.
The core pillar of our research is Mosaic, an app for decomposing thinking about hard questions into small subtasks. We compositionally build complex thoughts out of simple pieces. We want to get to the point where automated aggregation of individual thoughts leads to something that is more than the sum of the pieces.
Humboldt talked about natural language as a system that "makes infinite use of finite means" -- an infinite number of sentences can be created using a finite number of grammatical rules. As engineering team lead at Ought, you're working on mechanisms that have similar flexible compositionality.
We'll pay a $5,000 referral bonus to whoever refers the person we end up hiring (careers@ought.org, terms: https://bit.ly/2lw3Q8w). Our benefits and compensation package are at market with similar roles in the Bay Area.
Apply here: https://ought.org/careers/engineering-lead
We're a non-profit AI research lab. Our goal is to make machine learning solve tasks where success can’t be reduced to a simple metric. We're working towards a future where ML is as helpful for open-ended questions like “Should I get this medical procedure?” and “What career is right for me” as it is for optimizing ad click-through rates.
The core pillar of our research is Mosaic, an app for decomposing thinking about hard questions into small subtasks. We compositionally build complex thoughts out of simple pieces. We want to get to the point where automated aggregation of individual thoughts leads to something that is more than the sum of the pieces.
Humboldt talked about natural language as a system that "makes infinite use of finite means" -- an infinite number of sentences can be created using a finite number of grammatical rules. As engineering team lead at Ought, you're working on mechanisms that have similar flexible compositionality.
We'll pay a $5,000 referral bonus to whoever refers the person we end up hiring (careers@ought.org, terms: https://bit.ly/2lw3Q8w). Our benefits and compensation package are at market with similar roles in the Bay Area.
Apply here: https://ought.org/careers/engineering-lead
We're a non-profit AI research lab. Our goal is to make machine learning solve tasks where success can’t be reduced to a simple metric. We're working towards a future where ML is as helpful for open-ended questions like “Should I get this medical procedure?” and “What career is right for me” as it is for optimizing ad click-through rates.
The core pillar of our research is Mosaic, an app for decomposing thinking about hard questions into small subtasks. We compositionally build complex thoughts out of simple pieces. We want to get to the point where automated aggregation of individual thoughts leads to something that is more than the sum of the pieces.
Humboldt talked about natural language as a system that "makes infinite use of finite means" -- an infinite number of sentences can be created using a finite number of grammatical rules. As engineering team lead at Ought, you're working on mechanisms that have similar flexible compositionality.
We'll pay a $5,000 referral bonus to whoever refers the person we end up hiring (careers@ought.org, terms: https://bit.ly/2lw3Q8w). Our benefits and compensation package are at market with similar roles in the Bay Area.
Apply here: https://ought.org/careers/engineering-lead
We're a non-profit AI research lab. Our goal is to make machine learning solve tasks where success can’t be reduced to a simple metric. We're working towards a future where ML is as helpful for open-ended questions like “Should I get this medical procedure?” and “What career is right for me” as it is for optimizing ad click-through rates.
The core pillar of our research is Mosaic, an app for decomposing thinking about hard questions into small subtasks. We compositionally build complex thoughts out of simple pieces. We want to get to the point where automated aggregation of individual thoughts leads to something that is more than the sum of the pieces.
Humboldt talked about natural language as a system that "makes infinite use of finite means" -- an infinite number of sentences can be created using a finite number of grammatical rules. As engineering team lead at Ought, you're working on mechanisms that have similar flexible compositionality.
We'll pay a $5,000 referral bonus to whoever refers the person we end up hiring (careers@ought.org, terms: https://bit.ly/2lw3Q8w). Our benefits and compensation package are at market with similar roles in the Bay Area.
Apply here: https://ought.org/careers/engineering-lead