9 AI Techniques You Probably Haven't Tried
The AI Daily Brief: Artificial Intelligence News and Analysis - Nathaniel Whittemore
This episode of The AI Daily Brief explores nine lesser-known but impactful AI techniques that can enhance productivity and innovation. From
Key takeaways
- AI is driving real-world medical breakthroughs, such as a successful Phase 3 trial for an AI-assisted personalized mRNA cancer vaccine by Moderna and Merck.
- OpenAI's new private safety processing enables secure enterprise use of Frontier AI without data retention, addressing critical privacy concerns.
Main topics
- AI in healthcare: personalized cancer vaccines
- Enterprise AI safety and data privacy
Notable quotes
"It's a big deal for the field in general. With this positive study, there is a hope and likely investment to follow that these approaches may change the way we treat cancer more broadly." – Dr. Ryan Sullivan
Conclusion
While AI continues to evolve rapidly, the most impactful advances often come not from flashy new models but
Transcript preview
Speaker 1 (0:00) What if I told you you were using AI all wrong? Well, then I'd be lying, and I'd clearly be trying to get you to click on something by using an absolutely ridiculous and preposterous hook. But instead, what if I told you that there were nine AI techniques that were delivering some really awesome results to some people that you might not have had the time to try just yet? That would be a lot more true, because over the last couple of months we've seen a slew of new features and new tools become available like Claude's slash design and Codex's live voice mode and Grokbot's ability for a user to train it on an entire workflow by watching the screen. One of the things that makes AI so exciting is also the thing that makes it the most challenging, that it's changing all of the time. But today's episode is going to get you up to speed in no time at all. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. Speaker 1 (0:54) All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Blitzy, Harbor, and HyperAgent. To get an ad-free version of the show, go to patreon.com slash ai-dailybrief, or you can subscribe on Apple Podcasts. To learn more about sponsoring the show, send us a note at sponsors at ai-dailybrief.ai. And while you're on ai-dailybrief.ai, you can check out the link to next week's free webinar about agentic loops for knowledge workers. If you have heard me or others talk about loops as basically the second coming, but aren't exactly sure how to apply them to your work, this free webinar is for you. I will be there. Nufar Gaspar will be leading most of it. You can register for free. And even if you can't make it, we will send you the recording after. Again, all that information is at ai.dailybrief.ai. Well, my goodness, friends, the AI hype train is a hyping. But what is AI's real role in this story? Recently, there was a whole discussion between Anthropic CEO Dario Amadei and some of his critics about the tone of his messaging. One of Dario's responses to the critique that he had been overly negative was basically to say that it wasn't going to be marketing that changed people's opinions about AI. It was going to be AI actually delivering results. Specifically, he posted. I don't think that a glitzy marketing campaign with a positive spin is the way to win back trust. At this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive. The thing that will work is actually curing cancer. Which is why there were a lot of folks basically saying that that's what had happened yesterday. On Wednesday, Moderna and Merck announced a successful stage 3 trial for a personalized cancer vaccine, the first late-stage trial that's shown promise. the treatment functions very differently to chemotherapy-based approaches. Instead of blasting the cancer with radiation, the new method involves analyzing the cancerous cells, identifying the DNA mutation causing the cancer, and creating a personalized mRNA vaccine that can correct the mutation. The trial found the treatment was successful in more than 1,100 patients with advanced melanoma by extending their time in remission. Moderna and Merck have similar trials underway for lung cancer, and scientists hope the treatment can be applied to many different cancers. Dr. Ryan Sullivan, director of the Center for Melanoma and Mass General, said, It's a big deal for the field in general. With this positive study, there is a hope and likely investment to follow that these approaches may change the way we treat cancer more broadly. This gave rise to a lot of very excited posts from the AI community, like this one from Chubby. This is freaking huge, they wrote. For the first time, an AI-assisted personalized mRNA cancer treatment has succeeded in a phase 3 trial. Moderna and Merck sequence each patient's tumor and compare it to their healthy DNA. AI then helps identify which of the tumor's mutations are most likely to trigger an immune response. Absolutely incredible. Dario was right. Cancer will be cured in just a few years. Some, of course, took issue with the labeling of this as AI. Antibody 42 summed up the criticism saying, This is so dumb. They are using AI in place of machine learning because the distinction doesn't matter to people who don't care about reality. AI for mRNA design has been around for a while. It's not an LLM. And holding aside semantics, it is important to note that this is not scientists just plugging a bunch of results into ChatGPT and asking it to come up with a personalized cancer cure. I.e. cure cancer, make no mistakes. These are advanced machine learning methods that have more similarities to the technology underpinning AlphaFold. It's also frankly important not to lose the brilliant human scientists that are working with machine learning techniques to come up with these new treatments by simply attributing the breakthrough to AI. That said, I do also think it would be dismissive to say that this is just the AI hype train. Although it's still early days, this has genuine potential to be a major step towards curing cancer. And while it isn't directly related to LLMs and chatbots, this technology has still benefited greatly from all of the investment into compute, research, and talent over recent years. The AI era, LLMs or not, is setting the stage for some truly remarkable breakthroughs, and that is something worth celebrating. Certainly the market's celebrating it. Shabalur pointed out that Moderna stock was up 70 % after the announcement, rocketing up to 125 % growth just a few hours later. Said Elon Musk, so many breakthroughs are coming. Next up, a topic which seems extremely pedestrian next to curing cancer, but is extremely important for lots of enterprises. OpenAI has come up with a new safety technique that will allow them to offer Frontier AI without constantly monitoring their users. They're calling the process private safety processing and will be applying it to eligible API customers with zero data retention agreements. OpenAI says this will allow them to fulfill their promise of not retaining prompts or outputs after a request has been completed and ensure that sensitive corporate data is not available to OpenAI staff. Since the rise of long-horizon agents, safety monitoring has become much more difficult. Older system designs can only evaluate individual interactions, rather than assessing the entire arc of agentic work. Anthropic solution to this problem has been to simply disable zero data retention for Fable, gathering full data from each session to scan for harmful activity. For many enterprise customers, this is a complete non-starter and has shown up in fairly dismal adoption of Fable in the enterprise. OpenAI's new system extends automated safety scanning across an entire session, including customer-controlled data storage used for context and multiple agentic steps. This scanning is still fully automated and encrypted, meaning that no human ever lays eyes on sensitive data. If an issue is flagged, an OpenAI employee gets a summary of the activity with a category and severity rating, but stripped of any customer data. This means that false positives will no longer cause data exposure, as well as allowing OpenAI to develop more powerful models without the need for fully transparent review. The TLDR is that this is a change that could help make AI in the enterprise less of a trade-off around risk and security. OpenAI's head of product policy, Alia Howes, said, We've been talking to a bunch of enterprise customers and they really, really care about their enterprise data privacy and security. We've heard very loud and clear from businesses that this is important. They often have their own commitments that they have made to their customers. Summing it up, OpenAI staff member Adam GPT added, This is one of those small things that is actually a huge thing. And based on my ongoing conversations with enterprises around AI as well, That is absolutely true. OpenAI also announced a new partnership, providing the model for Replit's newly launched FreeMode. Now, despite the name, FreeMode isn't literally free. Instead, it gives users on the $20 a month plan the ability to use Replit without spending usage credits. FreeMode routes all queries through GPT-56 Luna, which Replit says will allow users to create 30 times more on their normal subscription. When Luna isn't enough for a complex task, users can still shift to another mode to select a more powerful model. But for everyday tasks like ideating or spinning up a slide deck, many are finding Luna to be more than enough. In their launch blog post, Replit wrote, AI models are now capable and affordable enough to make once-unreachable outcomes practical. And I think what's interesting to me is more OpenAI's focus on marketing and promoting 5.6 Luna as opposed to the specifics of this Replit partnership.