Databricks Co-founder Matei Zaharia Won ACM's Top Award and Said AGI Has Already Arrived

Matei Zaharia, co-founder of Databricks and creator of Apache Spark — one of the most influential computational frameworks in history — has become a laureate of the highest award of the Association for Computing Machinery (ACM). Upon receiving the prize, he made a statement that would sound like a marketing narrative coming from most, but not from him: AGI is already here, people just understand it incorrectly. Zaharia is not a startup founder making loud predictions for the sake of hype.

In 2009, he created Apache Spark as part of his doctoral dissertation at UC Berkeley. The distributed data processing framework quickly became an industry standard: today it is used by Amazon, Microsoft, Netflix, Uber, and thousands of other companies worldwide. It is precisely for this contribution to computer science that the ACM awarded him its highest prize in computing — an award that is often compared to the Nobel Prize in data science.

In 2013, Zaharia and his colleagues from Berkeley founded Databricks — a company that transformed Spark into a commercial enterprise platform and has grown to a valuation of 62 billion dollars. Today, Databricks competes with AWS, Google, and Snowflake for the corporate data and ML infrastructure market. In parallel, the company is actively investing in open language models — the DBRX series and investments in Mistral are evidence of this.

But more interesting than awards is his view on the current state of AI. In Zaharia's opinion, the main mistake in most AGI discussions is the framing of the question itself. People are waiting for an "AGI moment" as a single event: a model crosses some threshold — and everything changes.

But this is an incorrect framework. AGI is not a switch, but a process. Modern language models and agent systems already surpass humans in writing code, analyzing complex documents, and synthesizing scientific papers.

The question is not whether "we have achieved AGI," but how to use what already exists. Currently, Zaharia is focused on applying AI in scientific research. The AI for Science direction — accelerating drug development, automating laboratory experiments, analyzing genomic data — he considers the most important practical application of large language models.

According to him, the most promising application of LLMs is not chatbots and assistants, but research agents: systems capable of reading thousands of scientific papers, constructing hypotheses, and proposing specific experiments to test them. Zaharia's victory at the ACM is not just an honor for the creator of Spark. It is a reminder that the current AI revolution stands on the shoulders of the previous one — the revolution of distributed computing.

Spark gave the industry infrastructure for data processing at scale; now this infrastructure trains and runs language models. When a person who built this foundation says "AGI is already here" — this deserves more attention than another discussion about terminology.