Day: November 16, 2024

The S&P 500 (SNPINDEX: ^GSPC) is regarded by many as the best overall gauge of the U.S. stock market, as it includes the 500 largest publicly traded companies in the country. Given the breadth of businesses that make up the index, it is considered to be the most reliable benchmark of overall stock market performance. To be considered for admission to the S&P 500, a company must meet the following criteria:

• Be a U.S.-based company

• Have a market cap of at least $18 billion

• Be highly liquid

• At least 50% of its outstanding shares must be available for trading

• Must be profitable based on generally accepted accounting principles (GAAP) in the most recent quarter

• Must be profitable during the preceding four quarters combined

Palantir Technologies (NYSE: PLTR) is one of the most recent additions to the S&P 500, joining the benchmark on Sept. 23. That makes it one of only 11 companies to make the cut so far this year. Since the dawn of generative AI early last year, Palantir stock has surged 845%, as its expertise in the field drove robust revenue and earnings growth.

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Given the stock’s parabolic move higher, some investors are leery of Palantir’s lofty valuation. However, one Wall Street analyst believes this is just the beginning. Let’s take a look at what has fueled Palantir’s epic run, and if there’s additional runway ahead for growth.

Palantir has been developing cutting-edge AI solutions for more than two decades. The company earned its pedigree devising sophisticated algorithms to serve the U.S. intelligence, military, and law enforcement communities. Its systems developed the uncanny ability to connect seemingly unrelated data to foil terrorist plots and bring wrongdoers to justice.

The company has expanded beyond its humble roots, bringing the same data mining know-how to enterprise. Palantir’s AI and analytics systems dig through data and provide companies with solutions to real-world problems.

When businesses began clamoring for useable AI last year, Palantir was quick to develop its Artificial Intelligence Platform (AIP), a generative AI system that provided data-driven answers. The system leverages company-specific data to develop made-to-order solutions.

One of the primary stumbling blocks to adopting AI is that most companies lack the expertise to get started. Palantir developed a go-to-market strategy that takes that issue off the table. The company set up boot camp sessions that pair customer representatives with Palantir engineers to ensure they develop the AI solutions they need. This strategy has proven successful beyond the company’s wildest dreams.

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Prediction markets had a breakout moment during the presidential election, when they proved to be more accurate than most opinion polls.

So with various cryptocurrencies soaring since Donald Trump won the election, maybe prediction markets can accurately answer the question, “How high will Bitcoin go?”

On the crypto-based Polymarket, where the so-called French whale netted a massive post-election windfall, bettors have various options for Bitcoin, which is currently trading at about $91,000.

For a contract on what price Bitcoin will hit in November, the odds are 72% that it will reach $95,000. The price with the next highest odds is $105,000 at 23%, then $110,000 at 14%.

A separate contract that asks if Bitcoin will be above $90,000 on Nov. 22 shows 60% odds, while yet another contract asking if Bitcoin will reach $100,000 in November only has a 42% chance.

On the prediction market Kalshi, a contract that asks how high Bitcoin will get before 2026 shows 52% odds for $125,000 or above and 44% odds for $150,000 and above.

If prediction markets aren’t your thing, and you prefer a forecast from a more conventional Wall Street analyst, there’s Fundstrat Global Advisors cofounder Tom Lee.

Among the forecasters surveyed by Bloomberg, his stock market call in 2023 turned out to be the most accurate.

As for Bitcoin, he said in March that it could hit $150,000 by year-end. While that looks less likely now with just a month and a half left in the year, Lee told CNBC last week that “six figures” is still possible before the end of the year with more gains in 2025 in 2026.

“I think now because post-halving, Bitcoin is becoming a lot more relevant, and I think maybe the regulatory overhang is diminishing, there’s a lot of upside from here,” he explained.

Bitcoin has already soared 32% so far in November alone and has more than doubled this year. To get to $100,000, it would have to climb another 10%.

But there are signs that the post-election rally is stalling as the stock market notched a losing week. Still, key components of the “Trump trade” are riding high, like Tesla stock, Treasury yields, and the dollar.

Meanwhile, Quinn Thompson, the founder of the crypto hedge fund Lekker Capital, told Fortune this past week that he’s optimistic Bitcoin will attain the $100,000 milestone soon.

“I feel good that we hit it by year-end,” he said. “Very possible by end of month, but we’ll see.”

This story was originally featured on Fortune.com

It hasn’t even been two years since OpenAI changed the world by launching ChatGPT, but already there are signs that the technology could be hitting a ceiling.

OpenAI’s latest model, Orion, was designed to replace GPT and be a significant step beyond it, but the model has not hit the company’s performance targets. While it’s an improvement on OpenAI’s GPT models, it’s not the leap that the company had hoped it would be, and evidence is now piling up that artificial general intelligence (AGI) might be further away than technologists like OpenAI CEO Sam Altman had hoped.

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After all, OpenAI isn’t the only AI start-up experiencing such challenges. According to Bloomberg, the latest version of Alphabet‘s Gemini isn’t meeting internal expectations, and Anthropic, which is seen as the AI start-up most closely challenging OpenAI, is behind on the release of its updated Claude chatbot model called 3.5 Opus.

The biggest reason why these models seem to be reaching a ceiling is that they are having trouble finding new sources of substantial training data, as earlier models have exhausted resources like Wikipedia, social media, and news sites. Margaret Mitchell, the chief ethics scientist of AI start-up Hugging Face, told Bloomberg about the technological challenges: “The AGI bubble is bursting a little bit.”

In other words, until the problem of securing reliable training data sets is addressed, the anticipated performance of advanced AI models will likely fizzle out, at least in the near term.

It’s unclear how significant this slowdown is right now, but at a time when other industry insiders have called out an AI bubble, the news could reel in inflated stock valuations across the tech sector.

With the law of diminishing returns seemingly hitting the large language models (LLMs), the AI sector could take a hit, and Nvidia (NASDAQ: NVDA) seems to be the most at risk here.

After all, Nvidia’s graphics processing units (GPUs) are used to train AI models like ChatGPT, and demand for those components has skyrocketed since the launch of ChatGPT. Cloud-infrastructure companies, autonomous-vehicle companies like Tesla, and AI start-ups have stocked up on Nvidia’s chips in anticipation of an AI boom.

However, there’s still no “killer app” in generative AI, and the rap on the technology seems to be that it is impressive and capable, but the use cases aren’t fully clear, especially when it is still prone to mistakes.

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