100 AI Tools

Hey, AI Explorers! And welcome back to The AI Stream 🔥

Your new AI update is here, and it's packed with insights you won't want to miss.

This week's breakdown:

• DeepSeek-V3 launch

• Anthropic’s research on building effective agents

• Other updates in AI

• A list of 100 AI Tools

• Actionable guides we loved

Time to level up your AI game! Let's dive in 🚀

AI News

A New Open-Source LLM

DeepSeek, the Chinese AI firm backed by hedge fund High-Flyer, has released DeepSeek-V3, its latest open-source large language model.

Key Features of DeepSeek-V3:

• Performance: DeepSeek-V3 achieves a speed of 60 tokens per second, tripling the speed of its predecessor, V2.

• Architecture: The model boasts 671 billion mixture of experts (MoE) parameters, with 37 billion activated per inference, and has been trained on 14.8 trillion high-quality tokens.

• Benchmark Excellence: It outperforms open-source counterparts like Llama 3.1 and Qwen 2.5, and matches the performance of leading closed-source models such as GPT-4o and Claude 3.5 Sonnet.

• Cost-Efficiency: The development of DeepSeek-V3 was remarkably cost-effective, totaling around $5.57 million, compared to over $500 million spent on similar models like Llama-3.1. This was achieved through advanced training techniques and optimizations, making it an attractive option for developers seeking powerful AI without breaking the bank.

• Open Access: In line with DeepSeek’s commitment to open-source development, the model and its technical documentation are freely available to the public.

For developers and researchers interested in exploring DeepSeek-V3, the model is accessible via DeepSeek’s official website and GitHub repository

AI Agent News

Building effective agents

Anthropic’s latest research, “Building Effective Agents,” shares insights into creating large language model (LLM) agents that are both efficient and adaptable. Drawing from extensive collaborations across various industries, Anthropic talks about the effectiveness of simple, composable patterns over complex frameworks.

Key Takeaways:

• Defining Agents: Anthropic distinguishes between workflows—systems where LLMs and tools follow predefined paths—and agents, where LLMs dynamically direct their processes and tool usage.

• When to Use Agents: While agentic systems can improve task performance, they may introduce latency and increased costs. For many applications, optimizing single LLM calls with retrieval and in-context examples is sufficient.

• Frameworks and Tools: Anthropic advises developers to start with direct LLM APIs to maintain control and simplicity. If utilizing frameworks like LangChain or Amazon Bedrock’s AI Agent framework, it’s crucial to understand the underlying code to avoid potential pitfalls.

• Building Blocks: The foundation of agentic systems is the augmented LLM, enhanced with capabilities such as retrieval, tools, and memory.

Other AI News

AI Quick Hits

OpenAI has announced plans to transition from its current non-profit structure to a Delaware Public Benefit Corporation (PBC). This change aims to balance shareholder interests with public benefits, facilitating the necessary capital influx for advancing artificial general intelligence (AGI) that benefits all of humanity.

IBM introduced AI-driven HR agents to streamline human resources operations, automating tasks like employee support and talent acquisition.

Google unveiled “Jules” an experimental AI-powered coding assistant designed to help developers identify and fix errors in their code.

Okta launched Auth for GenAI, a new addition to their Customer Identity Cloud that helps developers add secure login systems to AI applications. This tool makes it easier to manage user identity and access in AI-powered software.

Salesforce has introduced Agentforce 2.0, an advanced digital labor platform designed to augment enterprise teams with autonomous AI agents. This update features a new library of pre-built skills, improved reasoning capabilities, and integration with Slack.

Anthropic has unveiled “Best-of-N (BoN) Jailbreaking,” a straightforward black-box algorithm designed to bypass safety measures in advanced AI systems across various modalities. By generating numerous prompt variations—such as altering text capitalization or shuffling words—BoN seeks to elicit unintended, often harmful, responses from AI models

The One AI Thing

100 AI Tools

Here is the list of 100 AI tools to boos your productivity across 20 categories:

Content Corner

Useful Links & Resources

Why AI agents grow:

An AI medical image diagnosis agent :

Turn a YouTube video into a full tutorial and ask follow-up questions:

New AI Tools

Top 5 AI Tools To Try

1. Jason AI > An AI sales assistant by Reply that helps sales teams write personalized emails and follow-ups to get more replies and book more meetings.

2. NotebookLM > A free note-taking tool from Google that helps you understand complex documents by answering your questions and creating summaries.

3. Cursor > A smart coding editor that writes, explains, and fixes code right as you type - perfect for both beginners and experienced developers.

4. Gamma > Create beautiful presentations and documents by typing what you want - no more fiddling with design.

5. Lindy > Build AI agents in minutes to automate workflows, save time, and grow your business.

Before You Go

That's it for today!

That’s all for today’s issue. Thanks for reading & being here 🖖

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See you next time 👋

Best, Vlad