1/ AI exploded on the scene at the end of 2022, with applications like @OpenAI's ChatGPT taking the world by storm.
2023 is poised to be the most exciting year of AI yet! 🎉
Here's mine and @vivek7ue's look at the lay of the land + what might happen next...
👀🧵
2/ Let's first dive into what the industry looks like today.
We see 5 main categories:
⭐ Foundation Model Players
⭐ AI Frontend Startups
⭐ Copilot/LLM for X Companies
⭐ Tooling Companies
⭐ Big Compute Clouds
3/ ⭐ Foundation Model Players
These include @AnthropicAI, @OpenAI, @CohereAI, and @AI21Labs. All of these players will all have instruction following models that are more or less substitutes for each other. Their businesses will all be based on an API model.
4/ Their APIs will all converge to:
➡️ Generations
➡️ Embeddings
➡️ Fine tuning
➡️ Classification
They will all:
☑️ Recruit AI frontend startups
☑️ Use an “index YCombinator” business model
☑️ Outsource GTM to AI frontend startups
Quality of model 🤝 Loyal customers
5/ ⭐ AI Frontend Startups
These are companies like @jasper_ai_ and @copy_ai that are vertical specific “prompt engineering layers” on top of the foundation model players.
These companies will use APIs from the foundation model players to stitch together end user solutions.
6/ 💪 Strengths = User focus + GTM
Most of YCombinator’s 2023 vintage will be companies of this form (a large number being marketing tech companies).
They'll look like a dressed-up version of the enterprise SaaS companies from the last decade, w/ an “AI intelligence layer”.
8/ These will also include OG LLM companies like @cresta (enterprise chatbots) & @LiltHQ (translation).
All these companies will bet that task-specific LLM tech + deep understanding of user + product is how the market is won.
They'll need big capital raises to pull it off. 💰
9/ ⭐ Tooling Companies
These are classic shovel providers in a gold-rush and will include:
↪️ Labeling companies (@scale_AI, @HelloSurgeAI, @SnorkelAI)
↪️ Training infra companies (@MosaicML, Stronger Compute)
↪️ Inference infra companies (@gooseai_NLP) + many others
10/ ⭐ Big Compute Clouds
These companies (like GCP, AWS, @Azure and @Oracle) will:
✅ Wake up to the business opp that LLMs provide
✅ Compete aggressively to go up the value chain beyond being just “GPU compute providers”
Azure threatens to have run away w/ this game already.
11/ Over the next year, we expect to see multiple battles, consolidation, and splintering across these categories.
Stay tuned for tomorrow where we share our top predictions on how the industry will shake out in the year ahead…
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As search engines become answer engines, referral traffic will drop!
It’s happened before: Google featured snippets caused this on 10-20% of queries in the past.
This is dangerous for pubs unless they take control of their relationship w/their search overlords. 3 ways to this:
1️⃣ Don’t get crawled – Tough to do. Unless publishers band together, unilateral disarmament is hard for a single publisher to achieve against a monopoly.
2️⃣ Ask for payment for LLM inclusion – again, tough against a monopoly. (@Neeva is committed to pub revenue share)
We were the first company to launch cited summaries backed by actual data. With our real-time AI search and web crawling capabilities, we provide authoritative answers that you can trust.
No more hallucinations!
3/ And now, we're taking our experience to the next level with the launch of Citation cards.
Simply click on a sentence in our summaries and see a card with additional details, allowing you to fact-check AI in a user-first experience.