https://amalianegreponti.substack.com/p/we-all-hurt
“We all hurt in so many different ways, all the time, and pain will either change, or end,” wrote Audre Lorde in The Cancer Journals. During the past week, while billionaires were busy being petty, government and private-sector announcements about trillions of dollars in AI investments whirled. The overarching justification touted was “because it is already on the way to curing cancer.” What a lie.
Powerful men hate being called petty—because they are. This week’s protagonists in the world of tech and AI proved this on multiple levels. On X, Elon Musk repeatedly attacked Sam Altman over “Stargate,” Altman’s coup of securing a half-trillion-dollar investment for OpenAI. Altman retaliated, alternating irony with anger management (“just one more mean tweet and then maybe you’ll love yourself…”).
Then, unexpectedly if understandably, Satya Nadella, CEO of Microsoft—which is OpenAI’s partner (although for how much longer is anyone’s guess)—popped in to indirectly support Musk in casting aspersions on Altman, OpenAI, and the credibility of the half-trillion-dollar investment, a venture between SoftBank, Oracle, and OpenAI, announced by President Trump at the White House.
Musk continued launching grenades at Altman, dragging out of oblivion posts Altman had made against Donald Trump three and four years ago. Altman proceeded to publish a succinct mea culpa directed toward the new President, similar to the one enacted by Zuckerberg a couple of weeks earlier. Things escalated until the President himself had to intervene, explaining, more or less, that Elon Musk’s position on this investment cannot be entirely rational because he “hates” Sam Altman. He then expressed empathy for Musk (“I, too, hate some people”) but clearly—and diplomatically—concluded that Musk’s feelings are Musk’s own problem.
Additional context highlights the dangerous pettiness of these people making and brokering our future: only two days earlier, Deepseek, “an unknown Chinese company with a 5.5 million dollar budget,” released r1, an open-source AI reasoning model that overall seems nearly on the same level as OpenAI’s o1—yet at a tiny fraction of the cost. Engineers at many top AI labs, including Meta, are now “moving frantically to dissect it and copy anything and everything we can from it. I’m not even exaggerating.”
This makes the success of OpenAI and Anthropic’s endeavors even more imperative for us in the Western world. Because this, whether we like it or not, is about the US vs. China. (It is telling that r1 insists “nothing ever happened at Tiananmen Square.”)
OpenAI is days away from releasing o3, while Anthropic—according to more than rumor—has created a model similar to o3, perhaps even more powerful, given that it’s an iteration of Claude, whose multifaceted intelligence and appeal, even at levels supposedly similar to gpt4o, no one has yet fully explained. Anthropic allegedly hasn’t released its new model yet because it’s grappling with safety and ethical considerations.
Yet, the real enmity between the leaders of these two companies, as well as the different principles driving their actions, isn’t reassuring. From Davos, Amodei accused Altman of opportunism, dishonesty, and overhype, of creating a bad culture, and of being incredibly dangerous for being so blasé on the brink of superintelligence. Amodei also added that he’s more convinced than ever that human work will completely end in three years.
Few seem to be taking the implications of this seriously. For the time being, only one leader in the race to create ASI seems to actively care about using it mostly for medical purposes—to cure disease and stop human suffering: Demis Hassabis of Google DeepMind. Drugs designed and developed by AI at Isomorphic, Alphabet’s drug discovery subsidiary, are expected to head to trial by the end of the year. Not a moment too soon. “Many of us have family at death’s door; a decade is too long for them for longevity science to make an impact. We need to accelerate for all their sakes,” a head of an AI lab posted a few days ago. We are at our most human when we or the people we love are suffering.
This is why billionaires who become involved in endeavors under the aegis of government have to put on a show of moral legitimacy—of caring about what most of humanity cares about. Cue Larry Ellison. At the White House’s announcement of Project Stargate (which, as an AI expert wryly commented, will most likely lead to the end of human employment—though in the meantime there’ll be great American jobs), Ellison said that AI is already on the way to curing cancer. This is false and misleading.
Looking like a living ad for life-extension and rejuvenation, Ellison spoke of predictive diagnostics (a simple blood test that will be able to discern minuscule fragments of mutations in the blood and assess one’s future risk of developing cancer) and preventive treatment (a personalized mRNA vaccine that will protect someone at risk of developing a specific cancer from ever developing it).
He was apparently referring to Moderna’s personalized mRNA vaccine that, in partnership with Merck’s immunotherapy (pembrolizumab, marketed as Keytruda), cut the risk of recurrence or death by 49% in patients with stage III/IV melanoma following complete resection. He implied that, with the help of AI, this vaccine could be produced robotically within just a few days.
Let’s break it down:
- What Ellison said about predictive diagnostics.
This blood test has been around for over a decade. It’s known as a liquid biopsyand is non-invasive and risk-free. Currently, most liquid biopsies are used on patients with metastatic cancers who cannot be submitted to organ biopsies, and on people with a family history of certain cancers who have a high probability of developing them. The fear of false positives—and the subsequent regulatory and legal drama—has led most companies to shy away from early-prediction liquid biopsies.Some did not, though—and paid the price. One of the first multi-cancer early detection (MCED) tests that screens for many of the deadliest cancers (those that don’t have recommended screening today) was Grail’s Galleri test. Acquired by Illumina, it hit the market in 2016, using machine-learning algorithms to detect methylation patterns associated with cancer and, when found, to predict the cancer’s signal origin. It screened for multiple types of cancer in asymptomatic patients at stages so early they wouldn’t show up on any imaging.The reaction was immediate. The European Union’s regulators, alleging that the acquisition threatened competition in the market for cancer detection tests, moved to block it. The US’s Federal Trade Commission followed suit. They succeeded. In late 2023, Illumina was forced to unwind its acquisition of Grail. The biotech world received the message loud and clear: medical innovation—even when safe, non-invasive, and FDA-approved—is not okay. To this day, liquid biopsies aren’t part of regular clinical practice, and most insurance plans don’t cover them. - The personalized “preemptive mRNA vaccine for all cancers”.
It is neither preemptive nor for all cancers. It’s for patients with locally or distantly metastatic melanoma who have had their tumors surgically removed and are undergoing immunotherapy (with pembrolizumab—Merck’s Keytruda) as a systemic treatment. It’s worth noting that melanoma is the most immunogenic of all cancers. Although nearly every new cancer treatment does save or prolong the lives of a very small subset of patients, enhancing immunotherapy with a personalized antigen mRNA vaccine for the only cancer that so overwhelmingly responds to immunotherapy is hardly a feat—let alone a cure for cancer.The reality of BioNTech’s mRNA cancer vaccines—unconnected to AI and unmentioned, of course, because BioNTech is German, not American—comes closer to the hype. BioNTech is the company that co-developed the original COVID mRNA vaccine with Pfizer. It currently has five cancer vaccines for advanced or metastatic solid tumors (including completely non-immunogenic cancers) in phase one trials; another five vaccines in phase two trials for specific metastatic cancers (lung, head and neck, pancreatic ductal adenocarcinoma, colorectal, and melanoma) that have progressed despite treatment with immunotherapy and chemotherapy.Over the past five years, other companies have also worked on or trialed mRNA cancer vaccines targeting specific neoantigens. These were based on liquid biopsies of patients found to carry these neoantigens in their blood. And yet, very little has changed in the treatments and drugs actually available to cancer patients. There are various reasons for these bottlenecks, but lack of consistent government interest and insufficient private-sector funding are among the main culprits.
And it’s not just about cancer. CRISPR/Cas9, the gene-editing tool that won the 2020 Nobel Prize in Chemistry, was publicly revealed in 2012 in a paper by Jennifer Doudna and Emmanuelle Charpentier. CRISPR/Cas9, adapted from a naturally occurring genome-editing system that bacteria use to defend themselves against viruses, has its origins in research done in the ’90s (!) by Francis Mojica, who was studying the bacterial immune system. Doudna, Charpentier, and Mojica were all funded by universities—the private sector wouldn’t touch them.
Today, in 2025, CRISPR is everywhere—theoretically. Researchers can now buy CRISPR kits from private companies, do gene-editing experiments in their own labs, and produce a personalized cure for someone in a matter of mere days. But in practice, this isn’t happening because of money. Personalized medicine is currently accessible only to those who can afford it.
It’s for the government to use its power to persuade biotech, venture capital, and health insurance companies that it’s in their interest—alongside their trillion-dollar profits—to care about ending diseases and suffering.
