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Hindustan Times
11-05-2025
- Science
- Hindustan Times
Fraud it, till you make it: Silicon Valley's attraction to cons
It was at a CRISPR community event in Cupertino, that I overheard two scientists talking about the ethics of creating gene-edited embryos. As I expected, Dr He Jiankui was mentioned. The infamous scientist from China is in the Valley right now, looking for funding and support for a new commercial venture that is focused on lowering the risk of Alzheimer's disease through gene-editing research. Ever since CRISPR had made gene-editing simpler and cheaper, the scientific community across the world had brought out regulations to prevent unethical experimenting on editing humans. Dr He Jiankui gained international infamy in 2018 when he announced that he had used a CRISPR machine on human embryos at a Chinese university lab, resulting in the birth of two designer babies. Even at that time, as an article in Science revealed, he had had support from his international colleagues and the Silicon Valley. Once the controversy became global, however, the Chinese government portrayed He as a rogue actor as did his scientific colleagues in the USA and China. But Silicon Valley has a shorter memory, which is why He is here, seven years later. Dr He's story made me think about how VC firms in the Valley are constantly putting their money in risky, potentially illegal, irregulated ventures and so are vulnerable to scams and fraud. Just last year, when anyone who used the words 'AI' was getting funded, Devin AI was touted by its company Cognition AI as the world's 'first AI software engineer'. The hype helped the startup reach a $2 billion valuation before a software developer on Github checked and said the AI couldn't even execute basic engineering tasks and that the startup was using deception to pretend it could do tasks it couldn't. Regardless of the falsification and deception, VC firms continue to invest in the startup. Why? Perhaps its FOMO combined with the unique VC math. About 90% of the startups that VC firms invest in, fail. Sometimes the tech doesn't work, sometimes it's the model or the product, or their vision of the future. Investors in the Silicon Valley are used to failure and can take risks. What they're constantly looking for is a tech innovation so disruptive that it cannot be replicated easily and will have unlimited growth potential – giving them a unicorn and quite a lot of profit. Combine this tendency to take risks with an insane amount of money floating in the Bay Area. In 2024, VC Funds here raised about $70 billion according to data released by Pitch Book: All of them looking for the next ChatGPT. This hunger or desperation to invest in the next big thing, with the ability to take a risk on an emerging technology, leaves these investors vulnerable to being exploited by someone with a great story, at the right moment and with the right hype. Like CRISPR babies, or Sam Bankman-Fried who, if you remember, used the money that investors put into his crypto exchange to fund his own crypto trading – something illegal in most markets across the world. In 2021, Alameda Research was a unicorn and Bankman-Fried was Valley's much-loved rather nerdy crypto founder, famous for effective altruism, a twisted capitalist philanthropy that encourages people to make money and then give it away for charity. Everyone – from politicians to venture capitalists – called him a genius. Two years later, when the crypto market crashed, Alameda Research filed for bankruptcy and the scam broke out. Hundreds of thousands of customers lost their investments, Silicon Valley Bank, the second largest bank in the country went bankrupt. And criminal charges were filed against Bankman-Fried and others in his inner circle. It's not that Bankman-Fried wanted to defraud. The Valley had taught him that it was important to break rules and things, and move fast. He had done what he had learnt and been rewarded for. And he probably had been under extreme pressure to perform. Once founders get funded, even the most ethical ones are under extreme pressure not only to build the innovation itself, but also grow rapidly and 'fake it till you make it'. The latter, an ethos to prioritize appearances and hype over substance encourages inflated valuations and unsustainable practices. Mostly it means lying through your teeth. One of the oft-quoted scams in this category is that of Elizabeth Holmes, founder of a healthcare startup Theranos. Holmes started the company when she was 19 and claimed she had developed a new technology that could run a multitude of tests on human blood at a fraction of the cost of current technology. Even though, according to a New Yorker profile, Holmes' details about Theranos' technology were 'comically vague', in 2015, the company's valuation was $10 billion. Within three years, Holmes and one of her associates were found guilty and are currently in prison. These cycles of hype and crash are humdrum everyday part of the Valley's life. In April, after the controversy, Cognition AI slashed its price from $500 a month for an AI engineer to $20 monthly. It's currently valued at $4 billion, despite questions about its product. If you have a cool idea and can show the conviction to do it, there's a chance that someone in the Valley will fund it. Combine that optimism about technology, and you know that another scam is as likely as a new hype cycle. Till fraud do us part?
Yahoo
12-04-2025
- Business
- Yahoo
AI Still Struggles to Debug Code, But for How Long?
PCMag editors select and review products independently. If you buy through affiliate links, we may earn commissions, which help support our testing. If you're a programmer who is scared about AI taking your job, Microsoft's R&D division might have some promising news for you. Microsoft Research tested several top large language models (LLMs) and found that many come up short on common programming tasks. The study tested nine different models—including Anthropic's Claude 3.7 Sonnet, OpenAI's o1, and OpenAI's o3-mini—and assessed their ability to perform 'debugging,' the time-consuming process whereby programmers sift through existing code to find flaws that prevent it from working as intended. Microsoft hooked up the AIs to a third-party debugging assistant it created called Debug Gym and tested the AIs on a common software benchmark, SWE-bench. The study had mixed results, and none of the tools achieved even a 50% success rate, even with the help of Debug Gym. Anthropic's Claude 3.7 Sonnet was the best performer, managing to successfully debug the faulty code in 48.4% of cases. OpenAI's o1 achieved success 30.2% of the time, while OpenAI's o3-mini did so 22.1% of the time. Microsoft says it believes the AI tools can become effective code debuggers, but it needs "to fine-tune an info-seeking model specialized in gathering the necessary information to resolve bugs." The findings may provide some slight relief for worried programmers, as more of the tech world's largest names pivot toward using AI for coding. In October, Google announced it was using AI to write "a quarter of all new code." Meanwhile, AI startup Cognition Labs rolled out a new AI tool last year, dubbed Devin AI, that it claims can write code without human interference, complete engineering jobs on Upwork, and adjust its own AI models. Meta CEO Mark Zuckerberg, meanwhile, told podcaster Joe Rogan that his company will "have an AI that can effectively be a sort of mid-level engineer that you have at your company that can write code" at some point in 2025, and he expects other companies will do the same.
