Amlan Patnaik

[Amlan Patnaik @Patnaik_amlan]

Probably Bhubaneswar's first @getdbt event!

Bhubaneswar Data + AI Meetup group has become a regular, engaging community of developers.

Join us for the next meetup!
https://t.co/oA2lSb2mf7

@dbt_labs + @duckdb #OpenSource #Data #AI #Bhubaneswar #developers

[LangChain @LangChain]

🦜🚀LangChain Templates Hub

With 60+ templates contributed by the 👪community and our 🤝partners, LangChain templates are the easiest way to start building with LLMs

But with so many, it can often be disorienting to know where to start

Today were launching 🚀LangChain Templates Hub🚀, an easy way to explore and get started

Explore them here: https://t.co/3xJWx9REMq

Includes:

❤️A way to "like" templates, so you can give your stamp of approval

📏A way to sort by popularity, so you discover community favorites

💼Tags for different use cases

🤝Tags with different integrations

✒️Information about the author

Includes top templates from @MongoDB @Redisinc @neo4j @TimescaleDB @tavilyai @pinecone @trychroma @thefireworksai @Ollama_ai @weaviate_io @AnthropicAI @awscloud @supabase @DataStax @elastic @replicate @cohere

We've also included a button to request a template - let us know what you'd like to see!

Explore them here: https://t.co/3xJWx9REMq

[Balaji @balajis]

Satya wins.
Reflexes of a startup CEO.
Resources of a trillion dollar company.
Pulls this together in 48 hours from a cold start.
Gets it signed and over the line before markets open.

[Rishabh Srivastava @rishdotblog]

Incredibly excited to launch Agents today! Agents automate complex, repetitive work in SQL, Python and R - all while keeping data scientists in the loop for feedback and clarification.

We built Agents to help with the many tedious trial-and-error tasks involved in statistical analysis, like feature engineering. Agents can test different models, parameter settings, and data slices to find the best solutions.

A key capability is that they can decompose complex, multi-step questions into discrete tasks that can be addressed by appropriate AI models.

For example, if asked "What customer segments have declining usage of product X?", the agent can break this down into SQL queries to segment customers, analysis of usage trends with time series models, and application of clustering algorithms.

We designed Agents to augment human intelligence, not replace it. The AI asks clarifying questions and produces reports with editing and collaboration built-in. This enables data scientists to work with the AI and colleagues to deliver results faster.

It's been fantastic to hear feedback from our alpha customers! I'm excited to get this in the hands of many more data scientists and analysts.

*Massive* kudos to @manshar_ for the incredible work that went into this!

[Chase Lean @chaseleantj]

You can use OpenAI's new DALL-E 3 image generator to make coloring book pages for your kids.

And it's completely free!

Here's how to do it:

[Airbyte @AirbyteHQ]

Do you fear being left behind in the fast-paced world of data due to disjointed data sources and tedious integrations?

The @pinecone Airbyte Connector might be your lifeline. Dive in and stay ahead with seamless data transformations.

Data integration is more than just merging numbers; it's about connecting diverse data sources effortlessly. The Pinecone Airbyte connector is here to transform how businesses use data.

Why the Pinecone Airbyte Connector?

The Pinecone connector combines the versatility of Airbyte's many source connectors with Pinecone’s vector database expertise.

Essentially, it’s a universal adapter for all data integration tasks. This connector is designed for varied use cases, from enhancing semantic search to building recommendation engines.

Key Features of the Pinecone Connector:

♦️ Streamlined Integration: Easily connect with Airbyte's variety of source connectors.

♦️ User-friendly Configuration: Get started with just a few details, like the Pinecone API key.

♦️ Dynamic Embedding: Choose columns and let the connector manage real-time embeddings.

♦️ Incremental Sync: Only new data is processed, making embedding efficient.

♦️ Versatility: The open-source connector is adaptable and can integrate other embedding models.

[ISRO @isro]

Chandrayaan-3 Mission:
'India🇮🇳,
I reached my destination
and you too!'
: Chandrayaan-3

Chandrayaan-3 has successfully
soft-landed on the moon 🌖!.

Congratulations, India🇮🇳!

#Chandrayaan_3
#Ch3

[Ryan Johnson @ryanmjohnson]

I’ve been waiting so long for this moment. Our car-free Paseo, the central spine of the neighborhood, is open to the public.

[Rishabh Srivastava @rishdotblog]

We just open-sourced SQL Coder, a 15B param text-to-SQL model that outperforms OpenAI's gpt-3.5! When fine-tuned on an individual schema, it outperforms gpt-4. https://t.co/zgMT0C2g4q

The model is small enough to run on a single A100 40GB in 16 bit floats, or on a single high-end consumer GPU (like RTX 3090/4090) with 8bit quantization.

We are also open-sourcing our framework for evaluating LLM-generated SQL. SQL can be tricky to evaluate (see here for why: https://t.co/tYEabtnWyn). With rigorous, open and reproducible testing, we hope to advance the frontier of OSS text-to-SQL solutions.

The model weights have a CC BY-SA 4.0 license. You can use and modify the model for any purpose – including commercial use. However, if you modify the weights (for example, by fine-tuning), you must open-source your modified weights under the same license terms.

There's an interactive demo + link to Colab if you would like to play around with it. I'm always hungry for feedback! :)

Working on this was intense (a lot of 3AM git commits 😅). So grateful for our amazing team. @JP_smasher, @manshar_, @medha_basu, and @wendyaww are incredible to work with!

[V. Ramgopal Rao, Ph.D. @ramgopal_rao]

BITS programme plans to convert PhD research into start-ups
https://t.co/GzO3OHJ5YP

[Paul Graham @paulg]

I've now talked to multiple startups building things on GPT-4 that they say would not have worked on 3.5. Each new version, a bunch of new companies become possible. This is how technology in general works, but it has never been so conspicuous.

[Patrick Campbell @Patticus]

My favorite tool I learned hunting targets at the NSA:

"Journey of a Dollar" analysis.

Basically, when analyzing an industry the first step is mapping how a dollar flows through it.

I map out:
- Who touches the $
- How many they touch
- How long they sit

From this I'm able to know:
- Where power/gravity exists
- Which parts are vulnerable for a wedge
- If the industry's worth targeting
- Where to dig deeper

This works at the industry and company level.

For instance, I love mapping a businesses cash inflows and outflows to find areas of efficiency.

There's a lot more I could go deeper on.

If interesting, just reply with questions or enthusiasm and I'll oblige with more content. :)

[Amlan Patnaik @Patnaik_amlan]

@NayrhitB Great news. More power to you @nayrhit!

[Balaji @balajis]

India is now the #1 emerging market to invest in, according to 85 sovereign wealth funds and 57 central banks representing $21T in assets.
https://t.co/fp7h3YYoQx

[Sahil Lavingia @shl]

Some guys learn guitar, others learn to code.

[Michael Seibel @mwseibel]

The existence of previous failure doesn’t mean you should switch you idea. But basic intellectual curiosity should motivate you to try to understand what happened and what you can learn from previous attempts.

[Notion @NotionHQ]

Introducing the new Notion Projects 🎯

https://t.co/Hf87oVxvl8

[Amlan Patnaik @Patnaik_amlan]

🫶

[Satya Nadella @satyanadella]

The rate of diffusion of this next generation of AI is unlike anything we've seen, but even more remarkable is the sense of empowerment it has already unlocked in every corner of the world, including rural India.