Technology

1. Why companies are pulling back
2. NSA turns to Mythos
3. Voice vs. everything else
4. ‘The Jensen effect’
5. Is AI really taking jobs?

Tech execs should use this moment to redirect their focus on making people’s lives better, and mathematicians sound the alarm about AI.

By now the pattern is familiar. An AI lab builds something powerful, then warns the world about how dangerous it is. Meetings and hearings in DC prompt calls for regulation. The talk leads to little action. Repeat.

This cycle of reverse-psychology PR has left a lot of people freaked out and angry, blaming AI and technological progress for inflation and job losses. The latest example is Anthropic’s recent post on recursive self-improvement, which calls for a temporary “pause” to allow society to adapt.

Governments can regulate a lot of things. AI, so far, isn’t one of them — it’s moving too fast and is too difficult to define, let alone legislate in ways that allow progress while guarding against the downsides.

But this moment of collective angst shouldn’t go to waste. Instead of debating dystopian half-measures like universal basic income, tech executives looking to weigh in on all the implications of the tech could redirect their energy — and money — to things that actually make people’s lives better. Besides a better and less expensive healthcare system, here are a few ideas:

• A science renaissance. America has gotten behind on basic research and forgotten how to build. AI, robotics, and materials science could change that — but only if we set an Apollo-style national goal around it.
• A serious — and safe — global effort to collect human biological data. We only understand a fraction of how the human body works, and one of the biggest bottlenecks is data. We now have the ability to collect everything from DNA to proteomics to epigenetic biomarkers at scale. But outside of the UK, UAE, and China, almost no governments are tackling this. The result is that biological research moves orders of magnitude slower.
• A revamped electrical grid. The current US grid is vulnerable to natural disasters and cyberattacks, and it’s terrible at balancing the fluctuating loads that come with renewables and modern appliances. Tech companies are investing in new nuclear power, fusion, and battery technology. Directing more funding in these areas would do more than just enable data centers. It would create whole new industries, jobs, and economic development.

These aren’t complete solutions — each deserves serious policy development. But the fact that so many tech titans, elected officials, and political advocates seem to be ignoring these issues should provoke more outrage than whatever data center is breaking ground on the edge of town.

Companies struggle to measure AI’s ROI

Echoing throughout New York Tech Week this year were conversations from business leaders about AI’s ROI, as companies begin cutting back on token spending. CEOs are trying to prove to their boards that the cost is worthwhile during a time of “massive over-investment” industry-wide, IBM Vice Chairman Gary Cohn said Thursday. The world will need AI, but “the question is, are we going to need everything we’re building?” In an era of tokenmaxxing, Cohn said that so far, the ROI has “not been nearly as high as people might think.”

Others sang a different tune. Two startup CEOs told Semafor that companies are reducing their AI spending not because the tools aren’t useful, but because the results are too difficult to measure. Most of the costs for companies come from software engineering workflows, with the market for coding capabilities jumping sevenfold from 2024 to 2025, to $4 billion, according to Menlo Ventures. But it’s long been difficult to determine the ROI of software engineering. In the near term, the AI companies that will benefit are the ones that automate work that is measurable, like sales and customer experience, the two startup CEOs said. In the meantime, the best way for engineers to be free of the token leash is for companies to figure out how to measure the value of their tasks.

— J.D. Capelouto and Rachyl Jones

NSA turns to Mythos for hacking

The US National Security Agency is reportedly using Anthropic’s cutting-edge Mythos AI model for hacking. Mythos has not been publicly released because of its powerful abilities to detect and exploit software vulnerabilities, and instead is being offered to select institutions to help them build defenses. The NSA is apparently using it for offensive purposes even as the US government fights a legal battle against Anthropic. AI agents are increasingly ubiquitous on the web — Cloudflare said that most traffic is now AI-led, a year ahead of earlier projections, with a decent minority of them malicious bots; Iran is a hotspot for such activity. And while such bots lack Mythos’ cutting-edge capabilities, top open-source models are less than a year behind the frontier systems.

The biggest impact of Mythos was probably always going to be in the national security realm, where vulnerabilities are big business. One way to judge the Mythos effect is to see whether prices for these complete attacks (known as zero days) rise or fall. A model like Mythos could help the NSA make its own zero days in-house, without having to rely on mercenary hackers. But it could also help US adversaries patch those bugs faster.

— Reed Albergotti

AI customer service is not ready for prime time

Voice capabilities are the future of AI, but customer service is still proving a difficult test case. That’s not because the voices don’t work, but because the broader experience often doesn’t.

I went to an ElevenLabs pop-up in New York, where a robot powered by the company’s voice models took coffee orders and prepared the drinks with minimal human involvement (only to refill the coffee beans and milk). The voice was eerily human — when I first heard it, I assumed it was one. But it struggled to recognize my voice and lagged significantly — due to network issues, the ElevenLabs team told me. When talking to a voice model to order merchandise, it struggled to find my account under “Rachyl,” as it recognized me verbalizing my name as the more typical spelling of “Rachel.”

For several years, customer service chatbots have been touted as a key use case for AI. While the technology behind them will get better, they haven’t gained the trust of the average user who hears an AI voice and immediately requests a human agent, even if it means waiting longer for assistance. To be sure, ElevenLabs, worth $11 billion, is placing bets across many industries, from becoming the voice of the Czech government to generating the voiceovers for creators’ sponsored posts.

— Rachyl Jones

Jensen offers the new ‘Trump bump’

Jensen Huang’s magic touch isn’t limited to Nvidia. Shares of AI infrastructure provider Nebius, chip design company Cadence, and hyperscaler CoreWeave all rose as much as 10% this week after Nvidia CEO Jensen Huang complimented them on stage at a company event in Taiwan, according to an analysis from market-intelligence provider Hudson Labs. Nebius is a “world-class AI cloud,” Huang said on stage, while also highlighting a design partnership with Cadence.

It’s a new spin on the “Trump bump,” which has boosted shares across companies favored by the president. Micron shares are up 880% since Trump dubbed them a “great company” in August. Caterpillar, Ford, and General Motors have all seen their stocks rise by double digits since the president praised them. Ditto for Coca-Cola, which he commended for pledging to use cane sugar instead of corn syrup.

— Rohan Goswami

AI’s reputation as a job killer may be overstated

Robust reports this week from ADP’s payrolls survey and the monthly estimate of US job openings have cooled the idea that AI is killing an entire generation’s employment prospects. “It’s a typical low-hire, low-fire type of environment,” Recruit Holdings CEO Hisayuki “Deko” Idekoba told Semafor’s Andrew Edgecliffe-Johnson. In such moments, it’s normal for the youngest job applicants to struggle most. Data from the parent of jobs site Indeed shows little evidence of an across-the-board AI effect.

Even the “brutal” drop in demand for software engineers looks increasingly like IT companies adjusting their recruitment after a pandemic-prompted period of unusual growth, and Indeed has actually seen demand for developers tick up in the past six months. “When we just compare what AI can do [in] 2022 and today, this impact should be bigger today” if the technology were making software skills redundant, Idekoba says.

While the data indicates AI isn’t the cause of job market woes, young professionals are still blaming the technology — and anti-AI sentiment is on the rise.

They have landed interviews with Taylor Swift, A$AP Rocky, Olivia Rodrigo, and Bad Bunny by offering what most celebrity media won’t: no question approval, no topic restrictions, and years of credibility. On this week’s episode of Mixed Signals, the hosts of The New York Times’ Popcast show join Max and Ben to talk about the evolution of their two-decade-old podcast, killing the written review, and whether literacy is over.

Hundreds of mathematicians signed a declaration calling for the use of AI in math to be restricted. The academics are alarmed by “plausible but unreliable (or even incorrect)” AI-generated papers potentially flooding the literature, but they may also be unnerved by AI models’ recent success in resolving several longstanding math conjectures: They warn that AI will “disproportionately affect students and early-career mathematicians.” Quantum computing scientist Scott Aaronson warns that we may be in “the possibly last days of human relevance” in math — and other fields — and unless there’s some “magic human ingredient” which AIs lack, then human mathematicians’ role will be reduced to “deciding which questions we find interesting and then understanding AI models’ answers to those questions.”