Quotesby GlyphData quotes
37 quotes from 18 people
- As LLMs continue to scale up, the value of any particular source continues to diminish.
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- The obvious AI variant is to let your users opt in to training your model on their interactions with it. Many will resist that, but if some don't, the model they get to use will outperform the vanilla one used by the others.
- Our customers trust us to provide them with maximal control over their operations, data, and decisions. Their competitive advantage should never become the training data for future models.
- Second, intelligence isn’t in fact a perfect commodity, in part because applied intelligence makes itself smarter.
- If learning flows in only one direction, economic value converges toward the owners of the learning infrastructure rather than the creators of the knowledge itself.
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- In the AI age, the buyer risks giving away knowledge, just in order to use what they bought. You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful.
- In the cloud era, enterprises accumulated data. In the AI era, they accumulate learning.
- Every quote from Satya Nadella
- I think the reason it is relatively easy for open source and previous laggards to catch up to within months of the frontier is that data is the real driver of progress.
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- If you're a CFO and AI can't tell you why margins changed, or you're a sales leader, and it can't find your next upsell, that's not an AI problem, that's a context problem.
- With Cortex Code and Snowflake Intelligence, we are extending from the trusted foundation for enterprise data and context to become the control plane for the Agentic Enterprise.
- We're moving from a world where data professionals are assisted by AI to one where AI agents do the work, guided by humans. We are calling this Agentic Data Work. It will fundamentally change how enterprises make decisions.
- This past year has been transformative for every business, as the promise of AI became real, and Snowflake sits at the center of the enterprise AI revolution.
- Snowflake Intelligence, our enterprise AI agent, saw the fastest adoption ramp in Snowflake history and is transforming how businesses interact with their data, delivering real-time, actionable intelligence.
- All the pre-trained models are pretty much the same because they pre-train on the same data.
- I would’ve not thought, none of us thought that somehow this AI thing and a deep neural network at some scaling will suddenly become the thing that figures out the patterns, not some schematized data model.
- We’re building ghosts or spirits or whatever people want to call it, because we’re not doing training by evolution. We’re doing training by imitation of humans and the data that they’ve put on the Internet.
- This revolutionary new cloud service enables the tens of thousands of our database customers to instantly unlock the value in their data by making it easily accessible to the most advanced AI reasoning models.
- Snowflake delivered yet another strong quarter, with product revenue of $1.09 billion, up a strong 32% year-over-year...
- Every piece of software in the world, every application, every workflow, every AI-generated line of code ultimately depends on a database underneath. Along the way, we’ve completely reinvented how applications are built, but the underlying databases have changed very little since the 1980s.
- Neon proves it: four out of every five databases on their platform are spun up by code, not humans.
- And my take for example is that at the end of the day, a BI tool is a 2D structure that is trying to represent a very complex multidimensional world and if you can imagine a dataset with just like 10 or 12 dimensions, trust me, there’s no simple dashboard that can represent that.
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- You know what I think, I think it was a mistake to think of storage as a revenue stream.
- Because roughly speaking, if you put a chat bot in front of a person, one of the first questions they’re going to ask is, “What will my revenue be 15 years from now?”, which no model has any business answering.
- Every quote from Sridhar Ramaswamy
- We’re continually retraining dozens of machine learning models that optimize every part of the transaction flow over an economy-scale dataset. The resulting optimizations are big enough that businesses see them in their topline revenue figures. Businesses simply start making more money when they switch to Stripe...
- Today, Snowflake is the most consequential data and AI company in the world.
- We're ahead on computational power, thankfully, due to a lot of the export controls that the Commerce Department has put in place, and then on data, it's a little bit of a jump ball.
- Our obsessive drive to produce product cohesion and ease of use has built Snowflake into the easiest and most cost effective enterprise data platform.
- You should not export data to import intelligence...
- And if you, like, take the best model on the planet and let it loose on an arbitrary schema, the likelihood that it’s actually going to understand the nuance of what’s in there, close to zero.
- It would take you or me 170,000 years to just read through this at eight hours a day.
- We are successfully campaigning the largest enterprises globally, as more companies and institutions make Snowflake’s Data Cloud the platform of their AI and data strategy.
- I think we can start training models now with the scale of the data that is beyond what a human can experience in a lifetime. So I think this is the first unlocking step.
- Rather, workflows and user networks seem to be creating more durable sources of competitive advantage.
- Snowflake as the global epicenter of trusted enterprise data is well positioned to enable the growing interest in AI/ML. Enterprises and institutions alike are increasingly aware they cannot have an AI strategy without a data strategy.
- Data has gravitational pull, and given the vast universe of data Snowflake manages, it is no surprise that interest in data science, AI and machine learning is escalating while its uses are rapidly evolving.