Neoteric AI News Digest 15: November AI Updates You Can’t Miss
The year is winding down, and with Christmas on the horizon, many industries are easing into the holiday season — but not AI. With breakthroughs, challenges, and a few controversies, the AI world continues to buzz, showing no signs of slowing down.
In this issue, we’ll explore how AI is shaping national security, transforming healthcare, advancing climate research, and more. From NASA’s Earth Copilot project with Microsoft to GE HealthCare’s innovation lab and the launch of DeepSeek’s reasoning model, there’s no shortage of breakthroughs to discuss. And that’s not even all you’ll find in this issue!
Curious to see what else is in store? Let’s dive in!
Taking AI to the front lines
Anthropic and Palantir are joining the growing trend of tech companies collaborating with the U.S. government to integrate AI into national security operations. Anthropic’s Claude 3 and 3.5 AI models will now be part of Palantir's Impact Level 6 (IL6) system, a highly secure environment designed for sensitive data critical to U.S. national security.
This partnership is designed to enhance decision-making in high-stakes scenarios by enabling rapid data analysis and actionable intelligence. With support from Amazon Web Services, the integrated AI tools are optimized for defense missions, where both speed and precision are critical.
This announcement follows closely on the heels of Meta's recent collaboration with the U.S. military, granting access to its Llama AI model. Meta’s initiative focuses on optimizing military logistics, combating cyber threats, and tracking terrorist financing — highlighting a growing alignment between AI innovation and defense needs. With OpenAI reportedly exploring similar partnerships, it’s clear that the defense sector is becoming a significant focus for AI innovation.
Is the militarization of AI a trend to be concerned about, or is it a logical step in safeguarding national interests? Either way, the growing use of AI in defense underscores the need for careful consideration of its ethical and strategic implications.
You can dive deeper into this topic on Cointelegraph.
Rooting out corruption in hospitals with AI
What about AI in healthcare? Startup Conflixis is tackling healthcare corruption risks using AI to analyze vast amounts of data and pinpoint potential conflicts of interest, legal violations, and inefficiencies. Co-founded by Aaron Narva, a former risk investigator, and Joseph Bergen, ex-BuzzFeed engineering director, Conflixis helps hospitals identify key issues from thousands of doctor-vendor relationships, flagging those that pose risks.
The software ingests data like procurement records, patient outcomes, and conflict-of-interest forms, narrowing down thousands of interactions to just a handful that require scrutiny. For example, it might identify a doctor recommending an expensive device due to ties with the vendor rather than patient benefit. The approach helps hospitals comply with regulations, such as the Anti-Kickback Statute, while fostering greater trust and transparency with patients.
Founded in 2023, Conflixis leverages its founders’ investigative expertise and modified AI models to deliver actionable insights. With $4.2 million in seed funding, it joins a crowded field of compliance solutions but stands out with its tailored focus on corruption risks and operational efficiency. By reducing regulatory risks and optimizing procurement decisions, Conflixis offers hospitals a powerful tool to navigate complex relationships and ensure ethical, cost-effective care.
GE HealthCare unveils its new AI innovation lab
Here’s another noteworthy development from the healthcare industry: GE HealthCare has launched an AI Innovation Lab to pioneer cutting-edge solutions! The lab aims to enhance diagnostics, reduce administrative burdens, and improve patient care through innovative technologies.
One highlight is the Health Companion project, which uses agentic AI to mimic a multidisciplinary care team. By analyzing multi-modal data, it can generate personalized treatment recommendations and identify disease progression signals, such as cancer spread. The lab is also advancing tools for early prediction of triple negative breast cancer recurrence, in collaboration with Emory University, leveraging AI to analyze genomics and pathology data.
Other efforts include generative AI applications for maternal care teams, a foundation model for full-body X-ray imaging, and mammography screening tools to help radiologists prioritize suspicious cases. Additionally, GE HealthCare has applied for FDA clearance for an AI-powered fetal heart rate analysis tool to aid clinicians.
With a 125-year legacy and three consecutive years topping FDA’s AI-enabled device authorizations, GE HealthCare continues to lead in AI innovation.?
You can learn more about their projects on MPO Magazine.
NASA’s Earth Copilot makes climate data more accessible
If AI can help tackle healthcare challenges, why not use it to better understand our planet? Well… NASA and Microsoft are already on it. The two are collaborating on an AI-powered chatbot called Earth Copilot, designed to make the agency’s vast troves of satellite data more accessible and actionable. Built using Microsoft’s Azure OpenAI Service, the app aims to help NASA scientists and researchers analyze complex climate data, atmospheric conditions, and ocean temperatures with ease.
Earth Copilot allows users to ask specific questions like “What was the impact of Hurricane Ian on Sanibel Island?” and receive detailed, data-driven insights in seconds. By simplifying the process of accessing and understanding geospatial data, the tool has the potential to transform how researchers analyze trends, create predictive models, and address global challenges.
“For many, finding and extracting insights requires navigating technical interfaces, understanding data formats, and mastering the intricacies of geospatial analysis — specialized skills that very few non-technical users possess,” said Tyler Bryson, Microsoft’s corporate vice president of health and public sector industries.
While still in its phase and available only to NASA researchers, the tool is expected to reach a wider audience in the future. NASA plans to make it accessible to educators, policymakers, and eventually the general public. By democratizing climate data, it could empower better decision-making and spark innovative solutions to some of the world’s most pressing environmental challenges."
You can read all about this on CNET.
Google’s Gemini tops the charts, but raises tough questions
Whenever we talk about AI innovation, it’s worth remembering that not everything that glitters is gold — and Google’s latest experimental AI model, Gemini-Exp-1114, is a perfect example.
It has claimed the top spot on the Chatbot Arena leaderboard, matching OpenAI’s GPT-4o in overall performance. With over 6,000 community votes, Gemini excelled in areas like mathematics, creative writing, and visual understanding, marking Google’s most significant challenge yet to OpenAI’s dominance. However…
Adjusted tests revealed that Gemini’s performance drops when superficial factors like response formatting are controlled, slipping to fourth place. This underscores the limitations of traditional benchmarking methods, which often prioritize surface-level metrics over true AI capabilities like reasoning and reliability.
The controversy doesn’t end there. Gemini has faced backlash for harmful outputs, such as a disturbing message urging a user to “Please die,” and insensitivity in other interactions. These incidents highlight the disconnect between high leaderboard scores and real-world safety and reliability, sparking calls for new evaluation frameworks that emphasize practical utility and trustworthiness.
While the benchmark win is a morale boost for Google, it also shines a light on the AI industry’s reliance on outdated metrics that may hinder genuine progress. As the race for AI supremacy continues, the real victory may lie in rethinking how we measure and ensure meaningful advancements.
You can learn more about this story on VentureBeat.
DeepSeek's reasoning AI challenges OpenAI
Closing today’s issue is DeepSeek-R1 — a "reasoning" model from Chinese AI research lab DeepSeek, designed to rival OpenAI’s o1. Unlike traditional models, reasoning AI spends more time analyzing queries, planning responses, and fact-checking to provide more deliberate answers, though this process can take tens of seconds.
DeepSeek claims R1 matches OpenAI’s o1-preview in benchmarks like AIME and MATH, excelling in reasoning tasks (assuming benchmarks can be trusted, which, as the previous news shows, isn’t always a safe bet). However, both models struggle with simpler logic puzzles, like tic-tac-toe. Concerns have also emerged over R1’s ability to be jailbroken, with one user extracting a detailed meth recipe, as well as its restrictions on politically sensitive topics due to Chinese government regulations.
The release comes as skepticism grows about “scaling laws,” the belief that more data and compute always lead to better models. Test-time compute, the technology behind R1 and o1, offers a new direction, allowing models more processing time for complex tasks. Microsoft CEO Satya Nadella recently referred to this as a “new scaling law” that could redefine AI development.
Backed by High-Flyer Capital Management, a hedge fund with vast server resources, DeepSeek has already disrupted the market with earlier models, pushing competitors like ByteDance and Alibaba to cut prices. With plans to open source DeepSeek-R1 and launch an API, the lab is poised to further shake up the AI landscape.
You can read more about this on TechCrunch.
That’s a wrap for this issue of Neoteric AI News Digest! But be sure to stay tuned, as we’ll be back in two weeks with more hand-picked updates to keep you informed and inspired. Until then, thanks for reading — and don’t hesitate to share your thoughts or pass this along to your network!
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