TheChek News Flow

Last week, OpenAI released its highly anticipated search product, ChatGPT Search, to take on Google. The industry has been bracing for this moment for months, prompting Google to inject AI-generated answers into its core product earlier this year, and producing some embarrassing hallucinations in the process. That mishap led many people to believe that OpenAI’s search engine would truly be a “Google killer.”

But after using ChatGPT Search as my default search engine (you can, too, with OpenAI’s extension) for roughly a day, I quickly switched back to Google. OpenAI’s search product was impressive in some ways and offered a glimpse of what an AI-search interface could one day look like. But for now, it’s still too impractical to use as my daily driver.

ChatGPT Search was occasionally useful for surfacing real-time answers to questions which I would have otherwise had to dig through many ads and SEO-optimized articles to find. Ultimately, it presents concise answers in a nice format: You get links to the information’s sources on the right side, with headlines and a short snippet that confirms that the AI-generated text you just read is correct.

However, it often just felt impractical for everyday use.

In its current form, ChatGPT Search is unreliable for what people use Google for the most: Short, navigational queries. Queries shorter than four words represent the bulk of searches on Google; these are often just a few keywords that get you to the right webpage. They’re the kind of searches most people are barely even conscious they’re making all day, and it’s what Google tends to do very well.

I’m talking about “Celtics score,” “cotton socks,” “library hours,” “San Francisco weather,” “cafes near me,” and other queries that make Google the doorstep to the internet for billions of people.

My test run with ChatGPT Search was quite frustrating at times, and it made me conscious of just how many keyword searches I perform in a day. I couldn’t reliably find information using short queries, and for the first time in years, I actually longed for Google Search.

Don’t get me wrong, Google has declined in quality for the last decade or so, largely because it’s been flooded with ads and SEO. Still, I kept opening Google in a separate window during my test because ChatGPT Search couldn’t get me a correct answer or webpage.

Who would win: ChatGPT Search or short queries?

I typed in “Nuggets score” to check how a live NBA game between the Denver Nuggets and the Minnesota Timberwolves was going. ChatGPT told me the Nuggets were winning even though they were actually losing, and showed a Timberwolves score that was 10 points lower than it really was, according to a Google result at the same time.

Another time, I tried “earnings today,” to check the companies reporting quarterly results that could affect stock prices on Friday. ChatGPT told me that Apple and Amazon were reporting their results on Friday, even though both companies had already reported a day earlier. In other words, it hallucinated and made up information.

In another test, I typed in a tech executive’s name to find their contact information. ChatGPT showed me a summary of the person’s Facebook profile, and hallucinated a link to their LinkedIn page, which produced an error message when I clicked it.

Another time, I typed in “baggy denim jeans,” hoping to shop. ChatGPT Search described to me what baggy denim jeans were in the first place (a definition I didn’t need), and recommended I go to Amazon.com for a nice pair.

I could go on, but you get the idea. Broken links, hallucinations and random answers defined my first day using ChatGPT Search.

This was not an insignificant launch for OpenAI. Sam Altman praised the feature for being “really good,” even though he’s known for downplaying his startup’s AI capabilities. The reason this time is different may have something to do with search being one of the biggest businesses on the internet, and OpenAI’s version could be a real threat to its biggest competitor, Google.

To be fair, Google Search is a 25-year-old product and ChatGPT Search is brand new. In a blog post, OpenAI says it plans to improve the feature based on user feedback in the coming months, and it seems more than likely this could be a significant area of investment for the startup.

To its credit, ChatGPT Search is rather good at answering long, written-out research questions. Something like, “What American professional sports league has the most diversity?” isn’t a question you could easily answer with Google, but ChatGPT Search is pretty good at scraping multiple websites and getting you a decent answer in just a couple of seconds. (Perplexity is also pretty good at these questions, and its search product has been around for well over a year.)

Compared to the traditional version of ChatGPT, which already had web access, the search feature feels like a better interface for browsing the web. There are more clear links to the sources where ChatGPT gets its information now — for news stories, ChatGPT will be tapping the media companies that it’s been striking all those licensing deals with.

The problem is that most searches on Google are not such long questions. To really replace Google, OpenAI needs to improve these more practical, short searches people are already making throughout their day.

OpenAI is not shy about the fact that ChatGPT Search struggles with short queries.

“With ChatGPT search, we’ve observed that users tend to start asking questions in more natural ways than they have in the past with other search tools,” said OpenAI spokesperson Niko Felix in a statement emailed to TechCrunch. “At the same time—web navigational queries—which tend to be short, are quite common. We plan to improve the experience for these types of queries over time.”

That said, these short keyword queries have made Google indispensable, and until OpenAI gets them right, Google is still going to be the mainstay for many people.

There are a couple reasons why OpenAI might be struggling with these short queries. The first is that ChatGPT relies on Microsoft Bing, which is widely regarded as an inferior engine compared to Google. The second reason is that large language models may not be well suited to these short prompts. LLMs typically need fully written out questions to produce effective answers. Perhaps there needs to be some re-prompting — running short queries through an LLM as a longer question — before ChatGPT Search can do such searches well.

Though OpenAI has only now released its search product, Perplexity’s own AI search tool is already serving 100 million search queries a week. Perplexity has also been touted as a “Google killer,” but it runs into the same problems with short queries.

Aravind Srinivas, the CEO of Perplexity, discussed how people use his product differently compared to Google Search at TechCrunch Disrupt earlier this week: “The median number of words in a Google query is somewhere between two and three. In Perplexity, it’s around 10 to 11 words. So clearly, more of the usage in Perplexity is people coming and directly being able to ask a question. On the other hand, at Google, you’re typing in a few key words to instantly get to a certain link.”

I think the fact that people are not using these products for web navigation presents a bigger problem than OpenAI or Perplexity are letting on. It means that ChatGPT Search and Perplexity are not replacing Google Search for the task it’s best at: web navigation.

Instead, these AI products are filling a new niche, surfacing information that gets buried in traditional search. Don’t get me wrong, that’s valuable in its own right.

OpenAI and Perplexity both claim they will work on getting better at these short queries. Until then, I don’t think either of these products can fully replace Google. If OpenAI wants to replace the doorstep to the internet, it has to create a better one.

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The next few months will be crucial for obesity players Eli Lilly, Novo Nordisk and Amgen

In terms of recent stock-market frenzies, the Ozempic trade nearly tops the list, second only to speculation that artificial intelligence will soon be writing this column.

Powerful weight-loss drugs like Wegovy and Zepbound have driven nearly $1 trillion in market-capitalization gains, with most of those gains flowing to Eli Lilly LLY -1.30%decrease; red down pointing triangle and Novo Nordisk NOVO.B -1.11%decrease; red down pointing triangle, the dominant players in the obesity-drug market. Would-be challengers such as Amgen AMGN -0.29%decrease; red down pointing triangle and Viking Therapeutics VKTX 0.47%increase; green up pointing triangle have also seen their shares surge on promising data.

Two major factors have powered these gains. First, the health benefits seem genuine: Clinical trial data for GLP-1 drugs have shown not only impressive weight loss but also potential reduced risk of heart attacks and sleep apnea. Second, there is exploding consumer demand, being driven in part by the psychological gratification that many people experience as their weight drops. That has fueled huge patient demand that, until very recently, has outstripped supply while creating a booming industry for compounders and telehealth companies.

But with so much optimism now priced into these stocks, further growth will be more challenging. Already, Lilly and Novo stocks have begun to lose momentum. It isn’t that Wall Street doubts the massive opportunity to treat hundreds of millions of people with obesity worldwide; rather, investors are anticipating several pivotal commercial and clinical developments that could either keep the party going at nosebleed valuations or lead many to take a breather.

All eyes will be on Novo Nordisk when the Danish company prepares to report quarterly results on Wednesday. The fear on Wall Street right now is that after Eli Lilly reported a shocking sales miss with Mounjaro and Zepbound, a poor showing for Novo’s Ozempic and Wegovy—which are both based on the active ingredient semaglutide—could signal a broader slowdown for the industry.

Investors are also anxiously awaiting late-stage data from Novo’s experimental drug CagriSema, a combination of semaglutide and cagrilintide, which has shown greater blood-sugar control and weight-loss benefits in diabetic patients. Investor skittishness has sent Novo Nordisk’s U.S.-traded shares down 13% over the past six months. But if Novo can clear these coming hurdles, as well as close its controversial acquisition of a U.S.-based contract manufacturing firm, it could set the stage for a significant relief rally.

Amgen is also facing a critical moment that could help position the biotech as the most serious contender to join the current duopoly. Much is riding on midstage trial data expected by year-end. If all goes well for Amgen, it could have a drug in the market in about two years. The drug currently undergoing testing, while effective, is known to cause side effects like vomiting and investors will be eager to see how prevalent such symptoms are. A key advantage for Amgen could be convenience: The drug is being tested as a once-monthly injection, compared with weekly for the current drugs.

Amgen’s reputation as a skilled manufacturer strengthens its prospects, especially given the complexity of producing these weight-loss injections, says Evan Seigerman, an analyst at BMO Capital Markets. With current supply shortages, a treatment that requires only 12 injections a year could also offer a manufacturing edge, he adds.

In many ways, Eli Lilly still controls its own destiny as the largest player in this space. Its drug Zepbound is more potent than Wegovy and its pipeline of injectables and pills looks more promising, with late-stage results from orforglipron, its non-peptide GLP-1 pill, expected next year. Over the coming months, investors will be watching closely to see if Lilly can deliver commercially.

While Novo’s Ozempic has wide name recognition, Lilly’s Zepbound is less known. The company last week announced it will start advertising the drug to consumers. It will also need to step up its work with wholesalers and the entire medical apparatus, from insurers to doctors, to make sure people are able to access its drugs. Right now, many employers don’t want to cover them for obesity and doctors are still hesitant to prescribe them. If the company delivers another disappointing report early next year, the GLP-1 thesis could start to face some real cracks.

The roster of companies vying for a place in this lucrative market is extensive. In the next few months, investors are anticipating updates from several other big players—AstraZeneca, Roche and Pfizer—as well as from smaller biotechs like Structure Therapeutics, Viking and Zealand Pharma. And investors are still waiting for Merck, which needs to find a way to replace the expected decline of its cancer blockbuster Keytruda, to write a big check to get in on the action.

Tim Opler, a managing director of investment banking at Stifel, argues that the challenge for a Big Pharma acquirer is that they don’t just want to buy an asset with similar efficacy to Wegovy and are instead hunting for next-generation technologies. With Wegovy’s patent expiring early next decade, generics will follow, so to compete in obesity treatments long term, companies must push the frontier of innovation, much of which is being driven by early-stage firms.

While still in its early days, the obesity-drug boom has already generated substantial fortunes on Wall Street. The pressure is now on for reality to match those sky-high expectations.

France pushes Brussels to delay looming fines on carmakers

Mark Zuckerberg is continuing to explore energy deals amid a Big Tech arms race over artificial intelligence

Plans by Mark Zuckerberg’s Meta to build an AI data centre in the US that runs on nuclear power were thwarted in part because a rare species of bee was discovered on land earmarked for the project, according to people familiar with the matter.

Zuckerberg had planned to strike a deal with an existing nuclear power plant operator to provide emissions-free electricity for a new data centre supporting his artificial intelligence ambitions. 

However, the potential deal faced multiple complications including environmental and regulatory challenges, these people said.

The discovery of the rare bee species on a location next to the plant where the data centre was to be built would have complicated the project, Zuckerberg told a Meta all-hands meeting last week, according to two people familiar with the meeting. 

The blow comes as rivals Amazon, Google and Microsoft have all struck deals recently with nuclear power plant operators to fulfil rising energy demands from data centres as they race to train and maintain power-hungry AI models. One AI query consumes up to 10 times the energy of a standard Google search. 

Meta is continuing to explore various deals for carbon-free energy, including nuclear, one of the people said. Meta declined to comment.

Nuclear is increasingly viewed as a way to get stable, round-the-clock power during the AI wars between Big Tech groups.

However, it also has high upfront costs and takes a long time to build. The industry in the west has historically relied on Russia for nuclear fuel.

Critics also caution about the risks of the build-up of toxic radioactive waste, which has to be stored safely or it could severely harm both humans and the environment. 

In September, Microsoft announced it would revive the mothballed nuclear plant at Three Mile Island, Pennsylvania.

Amazon paid $650mn in March to put a data centre next to the Susquehanna Steam Electric nuclear plant, also in Pennsylvania.

Google, meanwhile, said last month that it had ordered six to seven small modular nuclear reactors from US start-up Kairos Power, becoming the first tech company to commission new nuclear power plants.

Zuckerberg is under pressure to prove to investors that his all-in bet on AI will bear fruit, as the company’s capital expenditures continue to rise given its investments in running servers and data centres to develop the cutting-edge technology. 

Zuckerberg told staffers at the all-hands that, had the deal gone ahead, Meta would have been the first Big Tech group to wield nuclear-powered AI, and would have had the largest nuclear plant available to power data centres, two people said.

One person familiar with the matter said that Zuckerberg has been frustrated with the lack of nuclear options in the US, while China has been embracing nuclear power. China appears to be building nuclear reactors at a fast clip, whereas only a handful of reactors have been brought online over the past two decades in the US. 

Meta said it had already hit “net zero” emissions in its operations since 2020.