The Artificial Intelligence floodinggates are being opened by Google
On the Unpredictability of AI: Why Artificial Intelligence is Great at Text Generation, Yet It Fails in Trying to Use It
There are some experts that feel compelled to warn that we might be building systems that we will struggle to control because of the astounding capabilities of the programs that power them. OpenAI’s chatbot is often astonishingly good at generating coherent text on a given subject, summarizing information from the web, and even answering extremely tricky questions that require expert knowledge.
Generally, those who stage such stunts come to two conclusions: These models are amazing, but they fall miserably short of what humans do best. The emails fail to pick up workplace nuances. The clones have one foot in the valley. Most damningly, these text generators make things up when asked for factual information, a phenomenon known as “hallucinations”’ that is the current bane of AI. The output of today’s models may have a soulless quality.
Google worked hard to tone down the chaotic streak of text-generation technology as it prepared the experimental search feature announced yesterday that responds to search queries with chat-style answers synthesizing information from across the web.
The smarter version of search does not use the first person or talk about its thoughts or feelings. It completely avoids topics that might be considered risky, refusing to dispense medical advice or offer answers on potentially controversial topics such as US politics.
In March, a group of big names in artificial intelligence wrote an open letter calling for a delay in creating machine learning systems that are more powerful than GPT-4. Pichai was not a signatory and said in his keynote speech yesterday that the company is currently training a new, more powerful language model called Gemini.
A source at Google tells me this new system will incorporate a range of recent advances from different large language models and may eclipse GPT-4. But don’t expect to get to experience the full power or charisma Gemini can offer. If Google applies the same chaos-taming methods seen in its chat-like search experiment, it may just seem like another surprisingly clever autocomplete.
GadgetLab Podcast: Podcasts on iOS, Android and Windows Phones (with an App link at the top of the Playlist)
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Julian Chokkattu can be found on Twitter @JulianChokkattu. LaurenGoode is a person. Michael Calore is @snackfight. Bling the main hotline at @GadgetLab. The show is made by someone named Boone Ashworth. Our theme music is by Solar Keys.
Source: https://www.wired.com/story/gadget-lab-podcast-597/
What are your thoughts about Zelda and what do you think about the future of earbuds? A brief guide for what to do when you’re going on vacation
Julian recommends going on vacation and also the new Legend of Zelda game. Lauren recommends Janet Malcom’s book Still Pictures. Mike recommends the JBL Reflect Aero earbuds.
Source: https://www.wired.com/story/plaintext-youre-probably-underestimating-ai-chatbots/
What was the most important product of tech? Your iPhone, or what was your first tech purchase? How did you become an Apple employee? Why did you start writing a column?
In the spring of 2007, I was one of four journalists anointed by Steve Jobs to review the iPhone. This was probably the most anticipated product in the history of tech. What would it be like? Was it a turning point for devices? I am happy to say that my review is not embarrassing because I know the device’s significance. I didn’t think that the eruption of hardware, operating system, and apps was going to have a huge effect upon our attention, but it did. (I did urge Apple to “encourage outside developers to create new uses” for the device.) I didn’t suggest to expect the rise of services such asUber or TikTok, or that family dinners would become display-focused. Of course, my primary job was to help people decide whether to spend $500, which was super expensive for a phone back then, to buy the damn thing. I wondered if I spent time fretting about the AT&T network or the web browser’s inability to handle flash in the review that I read now. That’s like quibbling over what sandals to wear just as a three-story tsunami is about to break.
A new and popular media genre that can be observed is prompt-and-pronounce. To be successful, the process is to attempt a task that is limited to humans and then take it to an extreme. Red Smith once said that writing a column is simple, you open a vein and bleed. But would-be pundits now promote a bloodless version: You just open a browser and prompt. (Note: this newsletter was produced the old-fashioned way, by opening a vein.)
Usually prompt-and-pronounce columns involve sitting down with one of the way- early systems and seeing how well it replaces something that was previously limited to the realm of the human. In a typical example, a New York Times reporter used ChatGPT to answer all her work communications for an entire week. The Wall Street Journal’s product reviewer decided to clone her voice (hey, we did that first!) and appearance using AI to see if her algorithmic doppelgängers could trick people into mistaking the fake for the real thing. There are dozens of similar examples.
Hans Moravec calls our digital successors the mind children, and in one sense, it’s scary. The failures are comforting in another way. Sure, AIs can now perform a lot of low-level tasks and are unparalleled at suggesting plausible-looking Disneyland trips and gluten-free dinner party menus, but—the thinking goes—the bots will always need us to make corrections and jazz up the prose.
