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How Gemini and LangChain can supercharge your time series data 

Google Cloud Tech
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Code → goo.gle/data-dash
Use these products in an Analytics lakehouse → goo.gle/jss-lakehouse-deploy
Scale your latency-sensitive applications with Bigtable on Google Cloud. Join Senior Developer Advocates, Billy Jacobson and Brad Miro, as they showcase how a Bigtable instance can easily process up to thousands of read/write tasks per second in order to capture and analyze data in real-time in this episode of Making with AI. Watch along and discover how Gemini and LangChain can unlock natural language querying of data and boost productivity today.
Chapters:
0:00 - Intro
0:30 - Meet the speakers
1:47 - Demo: Collecting racing car data
4:50 - Interview
8:27 - Wrap up
Resources:
Smart home company uses Bigtable cloud databases → goo.gle/4eU7QpD
MLB pitches new data uses with Google Cloud services → goo.gle/3zJRD68
Oden Technologies case study → goo.gle/4eWTeFN
Watch more Making with AI → goo.gle/MakewithAI
Subscribe to Google Cloud Tech → goo.gle/GoogleCloudTech
#MakingwithAI #GoogleCloud
Speakers: Billy Jacobson, Brad Miro
Products Mentioned: Cloud - Data Analytics - Bigtable

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3 авг 2024

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Комментарии : 5   
@googlecloudtech
@googlecloudtech 25 дней назад
🙋 Which services are you using for your latency-sensitive application? Are you using AI for analysis and querying? Let us know below!
@GabrielMadichie
@GabrielMadichie 7 дней назад
This is the future
@bijukrishnan7792
@bijukrishnan7792 24 дня назад
I was hoping to hear how Gemini can help with anomaly detection but I guess the academic papers are right, LLMs and even those adapted for Time Series are not really accurate.
@folatech4404
@folatech4404 24 дня назад
interesting can i test this out in codelab
@TheTAKOGIN
@TheTAKOGIN 23 дня назад
Gemini is poor at understanding time-series data. Even when I input a CSV file, I've never gotten a decent answer... The ability to use a large number of tokens is a disadvantage if the comprehension ability is poor. It's useless if it doesn't work. Improvement is needed!
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