Traders Are Making Bullish Bets on Nvidia Ahead of Earnings Call
The chip maker’s report of its results has become a major event on Wall Street
Nvidia’s much-anticipated earnings report on Wednesday has investors speculating whether it will reignite enthusiasm for the artificial intelligence (AI) trade. Many are preparing for significant movements in the stock, scooping up options that could yield gains if Nvidia’s shares surge by over 10% this week.
Nvidia, known for its graphics-processing units (GPUs) essential to AI systems like OpenAI’s ChatGPT, recently reclaimed its position as the world’s largest publicly traded company. The company’s stock has more than doubled in 2024, following a stellar performance in 2023, where it tripled in value.
This explosive growth has made Nvidia a focal point of Wall Street, with its earnings day being compared to key Federal Reserve meetings and critical economic reports in terms of market influence. Dubbed “Nvidia Day,” the event has inspired memes, viewing parties, and substantial, often high-risk, bets on the company’s stock.
More information about Nvidia’s skyrocketing stock
Genesis: AI, Hope, and the Human Spirit
Moderated by Graham Allison, Douglas Dillon Professor of Government, Harvard Kennedy School. Join us for a conversation with former CEO of Google, Eric Schmidt, about his new book, "Genesis: Artificial Intelligence, Hope, and the Human Spirit," co-authored with Henry Kissinger and Craig Mundie.
From the unprecedented opportunities of AI to revolutionize medicine, production, and even the human spirit, to the risk of dark applications that could crush millions of human beings and subordinate mankind, Schmidt and his colleagues stretch our minds.
AnyChat Brings Together ChatGPT, Meta, Google Gemini, and More For AI Flexibility
A new tool called AnyChat is giving developers unprecedented flexibility by uniting a wide range of leading large language models (LLMs) under a single interface.
Developed by Ahsen Khaliq (also known as “AK”), a prominent figure in the AI community and machine learning growth lead at Gradio, the platform allows users to switch seamlessly between models like ChatGPT, Google’s Gemini, Perplexity, Claude, Meta’s LLaMA, and Grok, all without being locked into a single provider. AnyChat promises to change how developers and enterprises interact with artificial intelligence by offering a one-stop solution for accessing multiple AI systems.
At its core, AnyChat is designed to make it easier for developers to experiment with and deploy different LLMs without the restrictions of traditional platforms. “We wanted to build something that gave users total control over which models they can use,” said Khaliq. “Instead of being tied to a single provider, AnyChat gives you the freedom to integrate models from various sources, whether it’s a proprietary model like Google’s Gemini or an open-source option from Hugging Face.”
More about how AnyChat fills a critical gap in AI development
Perplexity CEO On New AI-Powered Shopping Assistant, Competition In AI Space
Aravind Srinivas, Perplexity co-founder and CEO, joins 'Squawk Box' to discuss the company's most recent product launch, what products the new shopping assistant will be able to show, and much more.
French Startup Mistral Unveils New AI Models and Chat Features
French AI startup Mistral has released a slew of updates to its product portfolio as it looks to stay competitive in the cutthroat AI space. Mistral’s Le Chat chatbot platform can now search the web — with citations in line, a la OpenAI’s ChatGPT.
It’s also gained a “canvas” tool along the lines of ChatGPT Canvas, allowing users to modify, transform, or edit content, like webpage mockups and data visualizations, leveraging Mistral’s AI models.
“You can use [the canvas feature] to create documents, presentations, code, mockups… the list goes on,” Mistral writes in a blog post. “You’re able to modify its contents in place without regenerating responses, version your drafts, and preview your designs.”
In addition to all this, Le Chat can now process large PDF documents and images for analysis and summarization, including files containing graphs and equations. As of today, the platform incorporates Black Forest Labs‘ Flux Pro model for image generation. And Le Chat can now host shareable automated workflows for tasks like scanning expense reports and invoice processing; Mistal calls these AI “agents.”
More on Mistral’s new AI models and chat features on TechCrunch
Contrast | AI Agents and AI Assistants
Get ready to transform the way you work with AI assistants and AI agents!
Martin Keen & Amanda Downie dive into the differences between these two types of AI and how they're shaping the future of work. From AI assistants that help with routine tasks to AI agents that take on complex challenges, discover how these two types of AI are designed to improve business outcomes and drive automation.
I Tested Meta Ray-Bans vs Apple Visual Intelligence With Seven Prompts — Here's The Winner
Whether I’m shopping, hanging out with the fam, or staying productive, AI is my go-to solution to get stuff done. That’s why I couldn’t help but wonder how Meta Ray-Bans and Apple Visual Intelligence compare when it comes to seeing the world through an AI lens.
Ray-Ban Meta smart glasses are equipped with a 12-megapixel camera, open-ear speakers, and a microphone, enabling users to capture photos and videos, listen to music, make calls, and even livestream directly to platforms like Facebook and Instagram—all without reaching for their smartphones.
Apple Visual Intelligence is part of Apple Intelligence, which lets users with
an iPhone 16 series device leverage the iPhone's camera to provide users with detailed information about their surroundings. Here’s what happened when I went head-to-head with the two AI technologies.
More on the face-off between Meta AI and Apple Visual Intelligence
A Practical Guide to Efficient AI
In the past years, we’ve witnessed a whirlwind of AI breakthroughs powered by extremely large and resource-demanding models. And now, faced with actually deploying these models at scale, AI engineers and builders are left to pick up the pieces on how to improve latency and resource consumption practically.
In parallel, the on-device AI movement is heating up, imposing even more physical constraints on AI model deployment. In this talk, we will first identify key sources of inefficiency in AI models. Then, we will discuss techniques and practical tools to improve efficiency, from model architecture selection, to quantization, to prompt optimization.
Dr. Shelby Heinecke leads an AI research team at Salesforce. Shelby’s team develops cutting-edge AI for Salesforce products and academic research. Her team's work spans AI agents, LLMs, on-device AI, entity resolution, recommendation systems, and beyond. Shelby earned her Ph.D. in Mathematics from University of Illinois at Chicago, specializing in machine learning theory. She also holds an M.S. in Mathematics from Northwestern and a B.S. in Mathematics from MIT.
Thats all for today, however new advancements, investments, and partnerships are happening as you read this. AI is moving fast, subscribe today to stay informed.