1/ Yesterday, @vivek7ue and I outlined the companies best positioned to take advantage of AI's breaking dam.
Today, we're taking you through what the market looks like today + where it's headed this year.
🔖 Read on…
2/ 1️⃣ Compute clouds and foundation model players will collide. 💥
The compute clouds will all move towards making “LLM AI capabilities” (a feature of their platforms), causing the first and last categories of companies to converge.
3/ Predictions:
👉 @Microsoft already has its OpenAI investment
👉 @Google will join the rungs of the foundation model providers by exposing an LLM API via GCP
👉 @amazon and @Oracle will buy out one of the independent foundation model companies, or roll out their own models
4/ As for @SnowflakeDB and @databricks-style independent companies, it’s an open question if there will be any at the end of 2023.
What are your thoughts? 🧐
5/ 2️⃣ The CoPilot for X companies will find themselves competing with AI frontend companies that use foundation model APIs to beat them to market.
We’ll see this play out in search, RPA, programming and other categories.
6/ The jury will still be out on whether you need to invest in deep tech to succeed in these verticals, or can build a frontend business on top of the pure foundation API players.
We think it’s the former.
7/ 3️⃣ AI frontend companies + the foundation model players will battle for who gets to own the data flywheel.
To be long lasting, AI frontend companies will need to:
✔️ Strengthen their user workflow and problem specific data
✔️ Create fine tuned models on top of their own data
8/ They will face fierce resistance from the foundation model players, who will attempt to retain the data flywheel to themselves, and push the AI frontend companies to restrict themselves to ”prompt engineering”.
9/ 4️⃣ The tooling companies will find the going a bit hard.
The largest of the foundation models will turn out to be great for producing labeled data, often better than humans.
10/ But, AI labeling companies will compete with the large models they helped bootstrap.
Infra companies will find open source tooling continues to get better and the GPU compute availability situation becomes easier, eroding their advantage.
11/ Both these classes of companies will react by “moving up the value chain” to solve for business use cases and find themselves in competition with the “AI frontend companies” and the “CoPilot for X” companies.
12/ 5️⃣ @OpenAI will try to be both an API provider and a “CoPilot for X” company for many use cases.
This will lead to channel conflict and friction with its partner companies.
We will start to see the beginnings of rent seeking behavior.
13/ 6️⃣ Traditional enterprise companies like @salesforce, @ServiceNow and @UiPath will find themselves threatened by one of the “Copilot for X” or “AI frontend” companies who will promise automation to disrupt their existing business model.
They'll likely end up acquiring them.
14/ This year in AI could be one of the most exciting technological advances since the iPhone. 📲
We're excited for what's to come! 🙌
For more details see our blog: https://neeva.com/learn/2023-ai-predictions
Did we miss anything? What are your predictions? Let us know your thoughts!
Originally tweeted by sridhar (@RamaswmySridhar) on January 12, 2023.
