Sphinx AI retweeted
Behind every AI breakthrough is an infrastructure layer making it possible.
The @redpoint InfraRed 100 List is here, recognizing 100 transformative companies building that critical layer.
We’re thrilled to announce that 27 Lightspeed-backed companies have been included in this year’s list.
Congratulations to: @AnthropicAI, @AWNetworks, @chainguard_dev, @ClickhouseDB, @cyera_io, @databricks, @docker, @elevenlabs, @emergentlabs*, Eon, @exaailabs, @FireworksAI_HQ, @glean, @grafana, @inferact, @judgmentlabs, @mistralai, @nexthopai, @PatronusAI, @raindrop_ai, @reactorworld, ScaleOps, @semgrep, @getsphinx, @stripe, @supabase, and @temporalio.
Lightspeed is proud to back teams that are working to help power the future of intelligence.
*Emergent is a portfolio company of Lightspeed India Partners ("LSIP"), a separate and distinct investment advisory entity from Lightspeed Management Company, L.L.C. ("LSVP"). LSVP and LSIP are not a unitary enterprise.
Excited to announce Sphinx 2.0.
AI messes up on enterprise data. Sphinx makes it right.
Sphinx enforces data accuracy across all your AI tools. See how it works: sphinx.ai/blog/launching-sph…
Sphinx 1.0 is out now! Try it now at app.prod.sphinx.ai!
Sphinx AI retweeted
The best coding agents don’t understand data well enough to have good analytical instincts.
Claude 4.5 Opus (right) confidently fits a single line to data with clear structure. The code runs, but the result is shoddy.
Sphinx (left) is a real data scientist, not just a coder 👇
Sphinx 0.9 is out now, featuring several long-requested product improvements, as well as the first agentic results from our recently overhauled research efforts. Read more below!
Behind the scenes, we've been overhauling our agentic evaluation and alignment procedures, and users can expect many improvements to Sphinx's behavior, ranging from data science expertise to Jupyter notebook fluency.
We'll be sharing more details on our research results soon!
Read the full changelog here!
sphinx.ai/blog/sphinx-0-9/
Thank you to @Adyen and @huggingface for the DABstep benchmark. This work helps define what great looks like and raises the bar for everyone.
While Sphinx is moving away from DABstep as a primary benchmark after a test-set leak, we’ll still use it in a limited capacity. [1/2]
It's unfortunate to see this happen -- the point of climbing benchmarks is to help firms like ours deliver a better experience to users, not just to post fake high scores
See more on how Sphinx is working through the leak here: sphinx.ai/blog/goodbye-dabst…
0.8 is now LIVE and it's the largest update yet, featuring Plan Mode, new Anthropic-powered engines, Jupyter-aware file search, and MORE!
Sphinx also is now able to perform Jupyter-aware file search.
This is important because if your Jupyter server is hosted on a remote machine (like via Colab), your kernel will only be able to access that remote machine's file system. Sphinx understands this.
Lastly, we've doubled usage limits for all tiers of Sphinx, so that all users can experience using Sphinx more.
Check out the full changelog here!
sphinx.ai/blog/sphinx-0-8/
Sphinx AI retweeted
As we head into the long weekend, I’m excited to dive into a few pet data projects.
What’s making this ridiculously easy is Sphinx AI + the new Google Colab extension. In <1 min, I can spin up free GPUs for our best-in-class copilot. See how below!
Added bonus: it's all free 💸
No compute? No problem!
You can now use Sphinx with Google Colab's VS Code extension to build complex models and analyses in your IDE, all totally free and with no need for local resources!
See Sphinx build a CNN model on MNIST on a Colab GPU:
Sphinx is now even faster! And, we've improved the knobs for how autonomously Sphinx acts as it works alongside you.
sphinx.ai/blog/sphinx-0-7-5-…
Not all data agents are created equal.
LLMs are fundamentally bad at understanding data, and without a good representation of data they make mistakes that are obvious to a human.
This is what separates Sphinx from solutions where AI is bolted on to a notebook (1/N)
Even over a wide range of random scatterplots, frontier models only have a crude understanding of data! This is why Sphinx’s representation learning is critical to ensuring that data science gets done correctly.
See the full deep dive and more details on our blog!
sphinx.ai/blog/not-all-data-…






