- Big Data News Weekly
- Posts
- 🔝 The Rise of the Declarative Data Stack
🔝 The Rise of the Declarative Data Stack
🦾Plus: Sam Altman’s new company “World” introduced
Hey folks! Let’s get into Big Data and AI craziness…
In today's edition: What's Shaping the Future of Data?
🤖 How WHOOP Built and Launched a Reliable GenAI Chatbot
đź“ŠMulti Objective Optimisation in Suggestions Ranking at Flipkart
🔍Taming randomness in ML models with hypothesis testing and marimo
🚀 OpenAI launches Windows app for ChatGPT
đź““ Google's NotebookLM launches business pilot
🚀Dropbox launches Dash for Business.
đź’ˇ AI Tutorial:How to Convert One-Line Prompts to In-Depth Prompts
🤖 AI Tools and Data Tools to checkout
Although machine learning is one part of the greater AI market, it is the most commonly implemented form of AI and growing rapidly in business. The machine learning market reached a value of about $1.41 billion in 2020 and is expected to reach $8.81 billion by 2025, according to 360 Research Reports.
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Data stacks have come a long way, evolving from monolithic, one-fits-all systems like Oracle/SAP to today's modular open data stacks. This begs the question, what's next? Or why is the current not meeting our needs? As we see more analytics engineering and software best practices, embracing codeful, Git-based, and more CLI-based workflows, the future looks more code-first.
Boston-based WHOOP is on a mission to help its members understand their bodies and unlock their potential through a performance wearable, accompanying app, and 24/7 health data.
At the scale of Flipkart’s massive active user base, our autosuggest system prompts about a billion Search queries each day. This increases manifold during sale events such as The Big Billion Days. Autosuggest is a typical Information Retrieval (IR) system that matches, ranks, and presents search queries as suggestions to reduce the users’ typing effort and make their shopping journey easier
The behavior of ML models is often affected by randomness at different levels, from the initialization of model parameters to the dataset split into training and evaluation. Thus, predictions made by a model (including the answers an LLM gives to your questions) are potentially different every time you run it.
👨‍💻 Data Tools, Libraries
Experts.js
The easiest way to create and deploy OpenAI's Assistants and link them together as Tools to create advanced Multi AI Agent Systems with expanded memory and attention to detail.
Farfalle
Open-source AI-powered search engine.
Langtrace
Open Source & Open Telemetry(OTEL) Observability for LLM applications.
AI News:
Its and AI-powered universal search across work apps. You can find, summarize, and organize content with natural language queries. With Dash's universal search, you can find files and content across all your work apps from a single search box. No more remembering where that important document was stored or shared
Google has introduced new updates to its AI podcast tool, NotebookLM, enhancing its capabilities for both personal and business use. Users can now set custom instructions for generating "Deep Dive" Audio Overviews, focusing on specific topics or adjusting the expertise level for different audiences.
Sam Altman’s new company “World” introduced the latest version of its eyeball-scanning Orb. It will be powered by NVIDIA’s Jetson chip and feature a new design. World is also working to integrate its identity verification into other software to combat deepfakes.
OpenAI has launched a Windows app for ChatGPT, now available for users to try out. OpenAI released a Windows app for ChatGPT that ChatGPT Plus, Team, Enterprise, and Edu users can try early.
Rhymes AI openly releases Aria - the first open-source multimodal Mixture-of-Experts (MoE) model, outperforming Llama-3.2 and GPT-4o mini with 3.9B activated parameters and a 64k token-long context window.
AI Tutorial
How to Convert One-Line Prompts to In-Depth Prompts
If your AI outputs aren't hitting the mark, the issue might be the prompt. OpenAI's new prompt generator, available at no cost, transforms simple instructions into detailed prompts. Here's how you can try it:
Visit the OpenAI API and sign in using your ChatGPT credentials (top-right corner).
Head to the 'Playground' tab (also in the top-right).
Select the star icon on the right side of the 'System instructions' bar.
Enter your prompt in the pop-up box—something as simple as "write a blog post" works—and press 'Create.'
Copy the detailed prompt you get and paste it into your preferred LLM. Adjust it as needed.
🔥Top AI tools to increase productivity:
Bard Pdf revolutionizes the way you interact with PDFs.
SEOBy.ai helps you kickstart your marketing efforts and rank higher on search engines without spending a dime.
ChatPaper is a specialized reading assistant crafted for researchers and professionals,
Pact Monster uses AI for better meeting productivity
Trolly AI: Revolutionizing SEO Content Creation with Advanced AI Technology.
pre.dev accelerates idea to development.
Microsoft Copilot: The Multi-Task AI Assistant
View our database of all the best AI tools for your needs: aitoolsup.com
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