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All eyes were on Nvidias quarterly earnings announcement on Wednesday, as investors looked for signs of weakness indicating that the so-called AI bubble is about to deflate. In fact, Nvidia appears to be selling graphics processing unit (GPU) chips for data centers as fast as it can make them. On the call with analysts, Nvidia reported better-than-expected revenues of $57 billion for its October-ending quarter, a 62% increase over the same quarter last year. Revenues rose by $10 billion, or 22%, from the prior quarter. Perhaps most importantly, the company projected revenues of $65 billion in the current quarter. As a result, Nvidia shares rose 5% after the earnings were announced at market close on Wednesday. That bump created an additional $205 billion of market capitalization. Theres been a lot of talk about an AI bubble, Nvidia CEO Jensen Huang said in his opening comments on Wednesday. But from our vantage point, were seeing something very different. The bubble refers to the possibility that the stock prices and valuations of artificial intelligence companies have become disconnected from their earning potential. Investors also fear that the massive investments that Big Tech and AI companies are sinking into infrastructure like data centers wont be backed up by rapid AI adoption. Let me remind you that Nvidia is unlike any other accelerator companywe address every phase of AI, Huang said. Then he set out to show Nvidias current business within the context of some broad technological transitions that he says are happening all at once. Huang explained that business software that has traditionally run on CPUs is increasingly starting to run on accelerators, specifically the GPUs that Nvidia sells. He said many traditional business tasks are being done by generative AI systems, replacing classical machine learning for things like content suggestion, ad placement, and content moderation. He also said autonomous AI (such as self-driving cars) and AI agents (such as coding assistants) mark the beginning of yet another big transition: The transition to agentic AI is giving rise to new companies, new products, and new services. Our singular architecture enables all three of these transitionsacross all industries and all phases of AI, from cloud to enterprise to robots, Huang continued. In other words, Nvidia is set to ride these big waves to big-time chip sales well into the future. Worrying about a bubble today, he seemed to suggest, may be a little short-sighted. Company CFO Colette Kress said earlier in the call that both hyperscalers like Meta and Google, and top AI labs like OpenAI and Anthropic, continue to spend big on Nvidia chips. We are preparing for aggressive growth ahead and feel optimistic about our opportunity set, she said.
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E-Commerce
In planning meetings, in brainstorms, in the messy moments when decisions need to be made before all the information is in, AI is my copilot. But not in the cute robot helper way. I treat it like my sharpest strategist, fastest researcher, and most unflinching truth-teller. As the CEO of Quantious, a future-forward marketing agency that works with tech companies, my job is to stay fast, smart, and endlessly curious; not just for myself, but for my clients. Having executive-level AI by my side is how I operate at scale without sacrificing strategy or soul. Forget about the hype of AI. Lets talk about what it really takes to work smarter, experiment faster, and free up time to be a creative leadersomething that you cannot automate. 1. AI is my executive sparring partner When youre running a fast-growing company, youre constantly making judgement calls without all of the details. Most people want ChatGPT to flatter them. I want it to challenge me. I run new product ideas, positioning statements, and brand hypotheses through AI to surface the cracks I didnt see. I use it to model outcomes, debate assumptions, and yes, poke holes in the perfect plan I thought I had. Your team might be too polite to challenge you. AI wont be, if you train it well. Start every session with a persona, such as: You are my chief strategy officer. Your job is to challenge mediocrity and raise red flags. Train it over time by giving feedback: Thats too agreeable. Give me a sharper POV or This sounds like fluff. Get specific. And really push it to dig deeper instead of giving you a standard response: This idea solves the problem, but I dont think its the best solution. Push me toward something bolder or more efficient. How would someone with 10x my time/resources/experience approach it differently? You may be surprised where this back-and-forth can take you. 2. I use AI to protect my most valuable asset: Strategic attention The less time I spend on routine admin tasks, the more time I have to steer the ship. AI is my secret weapon for clearing out the clutter. I use Bluedot to record and transcribe meetingssaving me and my team hours in cleaning up and consolidating notes, and turning around recaps and next steps in minutes. And if I need a detail from the discussion, I can even query the transcript to get the info I need, and all the context around it. To start using AI for attention management, begin with one task you do often (summarizing docs, doing premeeting research, writing recap emails) and let AI take a pass. If you want to think strategically, you need space to think. AI gives it to you. 3. I never miss a market beat I don’t have time to read every analyst report or listen to every podcast (who does?!) but I need those insights. AI curates the signal from the noise. Perplexity Deep Research turns complex trend reports into briefs to share with my team, or even my clients. Waldo gives me market snapshots faster than a team of analysts. Ive also dabbled in AI-powered podcasts, which summarize the most important industry news so I can catch up while on the go. They supplement my other favorite podcasts, so Im always armed with the latest trends and biggest industry moves. 4. I baked AI into the org chart At Quantious, AI isnt a department. Its a utility, like Wi-Fi or electricity. Every team has access to tools like ChatGPT, Gemini, and Slack AI. Designers use it to explore creative variations. Ops uses it to document processes faster. Marketers draft content 10 times faster. The tech isnt the point. The enablement is. While not every team member taps into these tools on a daily basis, having them in the toolkit keeps the door wide open for experimentation. Ive said it before: AI has made remote work more productive, seamless, and well-documented. We dont just integrate AI into workflows; we integrate it into our collective intelligence. Because the point isnt to do more faster, it is meant to elevate how we operate, across the board. Remember, AI isnt the intern. Its your most strategic hire. The truth is: Your team doesnt need you to be a prompt engineer. They need you to be an AI-literate leader. AI is no longer a tool in your workflow. Its a seat at your table. Treat it like a trusted advisor, and youll make sharper decisions, faster, without sacrificing strategy or soul. Lisa Larson-Kelley is founder and CEO of Quantious.
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E-Commerce
Nvidia forecast fourth-quarter revenue above Wall Street estimates on Wednesday, betting on booming demand for its AI chips from cloud providers against the backdrop of widespread concerns of an artificial intelligence bubble. The results from the AI chip leader mark a defining moment for Wall Street, as global markets looked to the chip designer to determine if investing billions of dollars in AI infrastructure expansion had resulted in towering valuations that potentially outpaced fundamentals. The world’s most valuable company expects fiscal fourth-quarter sales of $65 billion, plus or minus 2%, compared with analysts’ average estimate of $61.66 billion, according to data compiled by the London Stock Exchange Group (LSEG). Shares of the AI market bellwether rose over 4% in extended trading. Ahead of the results, doubts had pushed Nvidia shares down nearly 8% in November, after a 1,200% surge in the past three years. The broader market has declined almost 3% this month. Still, analysts and investors widely expected the underlying demand for AI chips, which has powered Nvidia’s results since ChatGPT’s launch in late 2022, to remain strong. Nvidia CEO Jensen Huang said last month that the company has $500 billion in bookings for its advanced chips through 2026. Big Tech, among Nvidia’s largest customers, has doubled down on spending to expand AI data centers and snatch the most advanced, pricey chips as it commits to multibillion, multi-gigawatt build-outs. Microsoft reported a record capital expenditure of nearly $35 billion for its fiscal first quarter last month, with roughly half of it spent primarily on chips. Nvidia expects an adjusted gross margin of 75%, plus or minus 50 basis points, in the fourth quarter, compared with the market expectation of 74.5%. By Arsheeya Bajwa and Stephen Nellis, Reuters
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E-Commerce
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