Aspiring pizzaiolo, data hippie, fun dad, thinker and writer, amateur DJ https://nitter.cf/t.co/KA8ZfeYnoR
Bolingbrook, IL
Joined September 2007
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Franco Patano retweeted
We’d love to have Snowflake as a customer of our AI Gateway! my DM is open.
nitter.cf/Yuchenj_UW/status/2115…
Franco Patano retweeted
Databricks CEO Ali Ghodsi says if frontier models stopped advancing, it wouldn't matter for most orgs because enterprise AI is bottlenecked on context, not intelligence:
"There's no agentic work that's automated the whole enterprise. That has just not happened. Why is that? The real reason is the models are smart enough, but they just don't have the context that exists inside of any organization."
"They have not been in every meeting. They don't know what's in everybody's heads. They don't know all the processes. There's always a couple of employees who know everything in every organization. You go tap on their shoulder, and everybody's like, 'Oh my God, what would happen if he or she quits?'"
"If you just fused that and gave that context into the AI models, just the frontier today, I think there's so much productivity gains you could get for any organization on the planet."
"For that, we actually don't need smarter models... If the frontier doesn't advance, it doesn't actually matter for the vast majority of organizations on the planet. They're just so far behind in the adoption curve of actually automating things and getting value out of this stuff."
@alighodsi
Read the latest Profiles of the Future by @bhorowitz and @mikemcg0 on Databricks & the Future of the Firm: a16z.news/p/databricks-and-t…
Franco Patano retweeted
Databricks is default aggressive.
I don't think we should fight. The two companies are complementary. Since you're not doing this AI stuff, I really think Snowflake should consider getting its AI tokens through Databricks. You can get both cheap OSS models as well as frontier (OAI/Ant/Gemini/Grok) models from our platform. It all goes through Unity Gateway which has Smart Routing, Budgets, and Access Control. You can even use Omnigent with any harness, including CoCo. Most of our customers used this to reduce token spend ~30% last few months while token count went up. Genie lets you then track, control, manage that spend, all your financials, marketing, etc. Quick POC?
Franco Patano retweeted
I don't think we should fight. The two companies are complementary. Since you're not doing this AI stuff, I really think Snowflake should consider getting its AI tokens through Databricks. You can get both cheap OSS models as well as frontier (OAI/Ant/Gemini/Grok) models from our platform. It all goes through Unity Gateway which has Smart Routing, Budgets, and Access Control. You can even use Omnigent with any harness, including CoCo. Most of our customers used this to reduce token spend ~30% last few months while token count went up. Genie lets you then track, control, manage that spend, all your financials, marketing, etc. Quick POC?
Franco Patano retweeted
Can a single database architecture satisfy both vibe-coded and large scale enterprise apps?
The same approach makes small database ultra cheap to run and branch can also make a large one faster and easier to operate. We call this architecture Lakebase.
Pro tip: if you have Genie One desktop app installed in your Mac, Option + Spacebar will pull up spotlight light bar to start your next thread.
People often ask how Databricks does things internally. I decided to start a new thing, “Tales from inside Databricks”. Check it out and let me know what you think!
youtu.be/N_2DbeIwtiU?si=wqVn…
If you use automatic notes transcription like Gemini notes, I dare you to turn on Closed Captioning and in real time see why your AI gets confused.
What are your funniest mistranslations from AI?
We used to spend years learning and practicing how to write well, built spell checkers and punctuation checkers, then when finally built the ultimate writing checker, we reside to adding little mistakes so people dont think its AI slop.
What other oddities have you discovered?
Franco Patano retweeted
What does it take to run data behind products used by one billion people every week?
For @OpenAI, Databricks serves as a governed, multicloud foundation across Azure and AWS, powering analytics, marketing, finance, trust and safety, and critical security operations—from threat detection to incident response across high-volume infrastructure.
Beyond using Databricks as its underlying data platform, OpenAI is also a strategic partner. Through the partnership, business users already using ChatGPT Work can use Genie MCP to talk to enterprise data.
Explore how OpenAI runs data at scale on Databricks: databricks.com/customers/ope…
Franco Patano retweeted
An extremely important functionality for agents is to simply extract fields out of PDFs. This turns out to be harder than people think because LLMs are primarily trained on predicting the next tokens. This leads them to "autocorrect" things that they shouldn't autocorrect. We launched an AI Extract capability that just excels at doing just this task with very high accuracy (95% vs 87% for others) and extremely low cost. Check out this blog on how we did it. The function can of course be called directly from SQL and be used throughout the platform.
databricks.com/blog/databric…
Franco Patano retweeted
I got this question so many times today. "How can you grow 80% at $7B?"
The true answer is that we're finally seeing a breakthrough with AI agents starting to work in the enterprise.
The AIs have been super smart for a while, but have lacked basic context that's in people's heads, or in some SaaS system-or-record. A lot of organizations are deploying FDEs to capture this context, or Ontology, and feed it to the AI. This is labor intensive and expensive. We just automated that with Genie Ontology.
Once you have that enterprise context graph, an AI agent like Genie becomes magical. I find myself no longer waiting for answers from my CRO, CFO, CMO, CHRO etc, I just keep queuing up questions on the phone while sitting in meetings. It'd frankly addictive.
Our customers are starting to do the same, over 70% of all queries on the platform are now generated by Genie agents. This fuels more questions to the platform, which drives consumption, which drives revenue. That's the simple answer.
Franco Patano retweeted
Full post here:
databricks.com/blog/managing…
Franco Patano retweeted
Kimi K3 at 239 tokens/s!
Databricks is now #1 for Kimi K3 inference speed and latency on Artificial Analysis.
A huge 2.8T parameters model, it’s the largest oss model we’ve ever served. We make sure the GPUs go brrr at Databricks.
Franco Patano retweeted
@databricks has the fastest and lowest latency on Kimi K3 (max)! Great job by Databricks AI team!
artificialanalysis.ai/models…
Franco Patano retweeted
You may have heard that GLM-5.2 at 328 token/s is cool,
How about 392?
Databricks is now #1 in inference speed for GLM-5.2 on Artificial Analysis. It's a great model, and we did a lot of optimizations.
Franco Patano retweeted
𝐆𝐞𝐧𝐢𝐞 is now the most important way to do data analysis in Databricks. What's unique about it is its ability to extract semantics from your entire Lakehouse, enabling it to answer complex data questions that cripple agents without a deep data understanding. We've now added a Mobile version, added Unstructured data processing, as well as enabled it to operate on all your dashboards and notebooks. Check it out:
databricks.com/blog/next-gen…