SpaceX's swift addition to the Nasdaq-100 index is expected to unleash billions in passive buying, as brokerages kicked off coverage of the $2 trillion rocket and satellite company with largely bullish views. The Elon Musk-led company joined the index on Tuesday, less than a month after its stock market debut on June 12 - among the fastest inclusions ever - thanks to the Nasdaq's revised rules for newly listed companies looking to enter widely tracked benchmarks. However, shares of SpaceX fell 5.4 percent, reflecting a slide in high-momentum tech stocks, including Micron Technology, on concerns about the longevity of the AI boom. "There's nervousness about expectations being too high," said Mark Hackett, chief market strategist for Nationwide. "I expect that to continue until we get some earnings out."

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Elon Musk becomes world's first trillionaire as SpaceX soars in stock market debut Elon Musk on Friday became the world's first trillionaire after shares in his SpaceX rocket company soared during the biggest-ever stock market debut. The Tesla and SpaceX founder comfortably cemented his status as the world's richest man, with his total net worth standing at $1.11tn (£828bn) according to the Bloomberg rich list. It came as the rocket, telecommunications and artificial intelligence (AI) company listed on the Nasdaq stock exchange with a value of $2.2tn. The company said its shares would be offered at $135 each, but trading opened at $150 and briefly reached $176.50 in a show of investor enthusiasm for potential business related to space and companies associated with Musk. SpaceX shares closed on Friday at about $161.

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Adult content creators are having their performances used without consent. This is just one way that AI now threatens their rights and livelihoods. When Jennifer got a job doing research for a nonprofit in 2023, she ran her new professional headshot through a facial recognition program. She wanted to see if the tech would pull up the porn videos she'd made more than 10 years before, when she was in her early 20s. It did in fact return some of that content, and also something alarming that she'd never seen before: one of her old videos, but with someone else's face on her body. "At first, I thought it was just a different person," says Jennifer, who is being identified by a pseudonym to protect her privacy. But then she recognized a distinctly garish background from a video she'd shot around 2013, and she realized: "Somebody used me in a deepfake."

Apple's iPhone is unveiled at a press conference in central London in September 2007. When iPhone arrived in 2007, it didn't just change technology. It changed how we live. That same year, TIME named it the Invention of the Year and called it "the phone that forever changed phones." But what mattered most wasn't just what iPhone was, but what it made possible.

SpaceX combining with xAI would bring Elon Musk's rockets, Starlink satellites, the X social media platform and Grok AI chatbot under one roof. NEW YORK - SpaceX is exploring deals with other companies helmed by serial entrepreneur Elon Musk, leaving investors working through permutations between space, autonomous driving and artificial intelligence to analyze which combination makes the most sense. The rocket maker is in discussions to merge with xAI ahead of a blockbuster public offering planned for this year, Reuters reported on Thursday. The combination would bring Musk's rockets, Starlink satellites, X social media platform and Grok chatbot under one roof, according to a person briefed on the matter and two regulatory filings. The deal's value, timing or primary rationale could not be independently determined.

If you want to put people back on the moon, don't gut the agency in charge of getting them there. The senator wanted a promise. For the last six years--or maybe the last decade or quarter century, depending on how you count it--the United States and China had been locked in a space race, a contest to see which nation could put its people on the moon . Senator Ted Cruz wanted President Donald Trump's nominee to run NASA, Jared Isaacman, to pledge that the US would not lose. Cruz brought a little surprise to Isaacman's confirmation hearing last April. It was a poster of the moon. On one side stood three astronauts and a giant Chinese flag. On the other were two more figures in space suits, with the tiniest Stars and Stripes planted in the lunar soil . Cruz apologized for the imbalance. "My team used ChatGPT," explained the senator, who chairs the committee that oversees NASA. Then Cruz, with a bit more seriousness, asked Isaacman, "Do we have your commitment that you will not allow the scenario on the right of this poster to happen? That China will not beat us to the moon?" Isaacman, a billionaire entrepreneur who had paid for his own missions to space, replied, "Senator, I only see the left-hand portion of that poster."

The billionaire's involvement with the Trump administration and DOGE had deep impacts on Tesla's bottom line. But Elon Musk was still able to turn his attention to SpaceX. What a weird time to be Elon Musk. This year opened with the businessman turned political operator throwing what appeared, to Nazis at least, to be a . This spring, activists frequently congregated outside the showrooms of his automaker, Tesla, to protest his foray into the US federal government and cozy relationship with President Trump.

Kernel-based methods such as Rocket are among the most effective default approaches for univariate time series classification (TSC), yet they do not perform equally well across all datasets. We revisit the long-standing intuition that different representations capture complementary structure and show that selectively fusing them can yield consistent improvements over Rocket on specific, systematically identifiable kinds of datasets. We introduce Fusion-3 (F3), a lightweight framework that adaptively fuses Rocket, Sax, and Sfa representations. To understand when fusion helps, we cluster UCR datasets into six groups using meta-features capturing series length, spectral structure, roughness, and class imbalance, and treat these clusters as interpretable data-structure regimes. Our analysis shows that fusion typically outperforms strong baselines in regimes with structured variability or rich frequency content, while offering diminishing returns in highly irregular or outlier-heavy settings. To support these findings, we combine three complementary analyses: non-parametric paired statistics across datasets, ablation studies isolating the roles of individual representations, and attribution via SHAP to identify which dataset properties predict fusion gains. Sample-level case studies further reveal the underlying mechanism: fusion primarily improves performance by rescuing specific errors, with adaptive increases in frequency-domain weighting precisely where corrections occur. Using 5-fold cross-validation on the 113 UCR datasets, F3 yields small but consistent average improvements over Rocket, supported by frequentist and Bayesian evidence and accompanied by clearly identifiable failure cases. Our results show that selectively applied fusion provides dependable and interpretable extension to strong kernel-based methods, correcting their weaknesses precisely where the data support it.