AI 🐰 Easter Edition

Hey Readers, Happy Easter!

In today's festive edition, we'll keep it short and sweet:

  1. My blog of the week: The 32 Biggest Mistakes Every AI Project Should Avoid

  2. AI news update: Meta's latest move in Computer Vision, Google's AI search touch, Anthropic's $5Bn bet, and OpenAI approach to AI Safety

  3. Interview: A Chat with Nirman from

Let's dive in!

πŸ“š AI Concept of the Week: The 32 Biggest Mistakes Every AI Project Should Avoid

AI has become an essential part of businesses worldwide, driving innovation and transforming industries. However, for AI projects to succeed, it's crucial to avoid some common pitfalls. This comprehensive guide will outline the 32 biggest mistakes that every AI project should avoid, helping business professionals ensure a smooth and successful implementation.

πŸ—žοΈTop news of the Week

Google CEO Sundar Pichai revealed in a Wall Street Journal interview that the company intends to incorporate conversational AI features into its search engine. The new features, based on Google's large language models (LLMs), aim to enable more natural user interactions. While specific details were not provided, Pichai mentioned the features would be available in the coming months. This shift signifies the increasing importance of AI in the tech industry, as Google also works on enhancing search personalization and relevance.

The Segment Anything project introduces a new task, dataset, and model for image segmentation, aiming to democratize segmentation and reduce the need for task-specific expertise, training compute, and custom data annotation. The project releases the Segment Anything Model (SAM) and the Segment Anything 1-Billion mask dataset (SA-1B), the largest segmentation dataset ever. SAM is a general, promptable segmentation model that can generate masks for any object in images or videos, even those it hasn't encountered during training. Potential applications include AI systems for multimodal understanding, AR/VR, content creation, and scientific study. The SA-1B dataset is available for research purposes, while SAM is accessible under the Apache 2.0 open license.

AI research startup Anthropic aims to raise up to $5 billion over the next two years to compete with OpenAI and enter more than a dozen industries. The company plans to develop a "frontier model," called "Claude-Next," which will be 10 times more capable than today's most powerful AI. This will require $1 billion in spending over the next 18 months. Anthropic is working on a next-gen algorithm for AI self-teaching called "constitutional AI," designed to align AI with human intentions. The frontier model could be used to build virtual assistants for various applications, potentially automating large portions of the economy. Anthropic, which competes with OpenAI, Cohere, and AI21 Labs, has already raised $1.3 billion, with Google investing $300 million for a 10% stake.

OpenAI is dedicated to ensuring AI safety and widespread benefits. ChatGPT users have reported increased productivity, creativity, and tailored learning experiences. OpenAI recognizes potential risks and incorporates safety measures at all levels. Rigorous testing, external feedback, and reinforcement learning are employed before releasing new systems. Real-world use helps improve safeguards over time, and OpenAI cautiously releases new systems with robust safety measures.

Protecting children and respecting privacy are priorities. Age restrictions and content limitations are in place, and personal information is removed from training datasets. Efforts are made to improve factual accuracy, with GPT-4 being 40% more accurate than GPT-3.5.

OpenAI believes in dedicating time to research and testing safety mitigations, as well as fostering collaboration and dialogue among stakeholders. Policymakers and AI providers must ensure effective global governance to prevent corner-cutting in AI development. OpenAI is committed to contributing to this challenging task.

πŸŽ™οΈ Interview of the week: A Chat with Nirman from

I spoke with Nirman Dave last year, the founder of, a no-code AI startup. They started their journey in an Airbnb garage and went door-to-door gathering feedback from data professionals to develop a user-friendly AI model creation tool. Nirman's background in machine learning and behavioral economics inspired him to develop this tool for business users. They have thousands of users who have built hundreds of thousands models, saving millions of hours in traditional data science work. Their mission is to make data science effortless without oversimplifying it. Nirman believes AI will become commoditized, allowing data scientists to focus on more complex tasks.

Thank you for taking the time to read! When you subscribed to this newsletter, my commitment to you was to be your helpful guide in navigating the world of AI. How did you find today's issue? Please reply to this email with your feedback and any suggestions for future topics.

See you next Sunday!

Armand 😎

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