Introducing TabFM in BigQuery: Predictive analytics reimagined

TL;DR

TabFM, a new pre-trained model for predictive analytics, is now available in BigQuery, allowing users to generate accurate predictions on tabular data without the need for extensive model training or tuning.

✦ Why It Matters

Start using TabFM in BigQuery today to streamline your predictive analytics without complex model management.

Key Takeaways

Use TabFM for quick predictions without model training.
Leverage SQL functions AI.PREDICT and AI.EVALUATE for ease of use.
Ideal for small-to-medium datasets and frequent data changes.
Consider traditional models for large datasets requiring custom tuning.

How It Works

TabFM employs in-context learning, similar to large language models, to generate predictions by interpreting historical data as examples. This allows it to make accurate predictions in a single forward pass without traditional training.

Introducing TabFM in BigQuery: Predictive analytics reimagined

Using OKF with Knowledge Catalog to serve context for agents

How Uber improves network reliability while unblocking cloud migration

Simplify your resilience testing strategy with Google Cloud Fault Injection Testing

Financially Motivated Threat Actor BREEZE COMET Targets Brazil

Using OKF with Knowledge Catalog to serve context for agents

How Uber improves network reliability while unblocking cloud migration

Simplify your resilience testing strategy with Google Cloud Fault Injection Testing

Financially Motivated Threat Actor BREEZE COMET Targets Brazil