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HHS Protect, started during Operation Warp Speed, utilized two Palantir programs. While documentation suggests planning began over a decade prior with Operation Stargate and CAIA databases, HHS Protect involved a partnership between the AMA, HHS, the CDC, and Palantir. Palantir developed a program that assigned individuals a threat risk score using a program called Tiberius, also used for other purposes. Medical coding programs with AI, like those from 3M and Epic, partners of Palantir, share data. Tiberius assessed compliance with lockdown measures, vaccination status, and masking, determining threat risk scores based on obedience. It also identified compliant areas by ZIP code and incorporated ethnicity into the risk assessment, as reported by Whitney Webb. Gotham, Palantir's AI kill chain program, used the threat risk score from Tiberius to execute AI-driven decisions on deploying countermeasures like vaccines, Remdesivir, and ventilators. HHS Protect monitored this process, identifying hospitals and patients based on algorithms to execute interventions via the Gotham program.

Digital certificates are needed for people working in nursing homes, hospitals, and schools to authenticate their vaccination status. Travel may also require such authentication. Pfizer broke every record in developing the vaccine.

In 2012, DARPA initiated the Adept Protect P3 Program, aiming to prevent pandemics using gene-encoded vaccines based on RNA or DNA. This approach was intended to stop a pandemic within 60 days. The development of vaccines under Operation Warp Speed, announced by President Trump, was not a new concept but had been in progress since 2012. The military, not Pfizer or Moderna, proposed the idea of messenger RNA vaccines. The military has various biological threat programs, including those for smallpox, monkeypox, and anthrax. The Emergency Use Authorization, initially designed for rapid military technology deployment, was first applied to the public during the COVID-19 pandemic.

Speaker 0 discusses Palantir and expanded government use. Key points: - Palantir is openly building databases on people, used with ICE and announced for broader government use; Palantir also manages all health data due to extensive contracts with HHS. - Trump’s first term included a push to have social media companies flag statements to prevent shootings, using analytics to determine intervention before a crime—concept described as “minority report.” - William Barr, during the first Trump administration, created DEEP, a program that legalized precrime in the United States; there were a few arrests under DEEP for Facebook posts, but not many, with the legal framework in place since Trump’s first term. - The pitch for a precrime system included HARPA, a health-focused version of DARPA, and a program called Safe Homes intended to analyze American social media posts for early warning signs of neuropsychiatric violence. Based on that analysis, individuals could be sent to a court-ordered psychologist or physician or placed under house arrest without having committed any crime. - With Palantir’s increased government integration, especially through the Doge agency led by Elon Musk, Palantir has embedded itself further in government, including the IRS and mortgage-related entities like Fannie Mae; this involves access to data from the Department of Treasury and the IRS, forming a master database aimed at stopping crime before it happens. - Palantir’s precrime activities included piloting predictive policing programs in police departments, initially in New Orleans, targeting primarily low-income minority neighborhoods. - Other companies besides Palantir, such as Predpol in Los Angeles, claim to provide predictive policing with an accuracy of 0.5%; contracts with Predpol have not been terminated. - The overarching concept traces to the Panopticon idea: constant surveillance leads people to police themselves and censor themselves, implying control through perpetual observation, rather than purely improved efficiency in policing. The speaker characterizes this as the foundational form of control.

The presentation examines the pattern of deployment of toxic vaccine batches using the VAERS dataset. It notes that the Covid vaccine was deployed in batches or lots, each with a number, and the batches are listed in VAERS in the order they were created, with adverse reactions recorded for each batch. A graph was produced with adverse reactions on the vertical axis and the sequence of batches in time on the horizontal axis, showing patterns of deployment in 2021. Each dot represents a batch, and the speaker highlights that about 95% of batches lie close to the x-axis, forming a thick line, with 80% of all batches generating only one or two adverse reaction reports and thus considered harmless. In contrast, the “clouds” and spikes above the x-axis represent toxic batches, with all such dots categorized as toxic. The breakdown given is: - 5% of all batches belong to these clouds and spikes. - The truly toxic batches generate 1,000 to 5,000 adverse reaction reports and are found above a red line, causing harm across every state in the USA where deployed. - These very toxic batches comprise about 0.65% of all batches (roughly one in 200). Total batches deployed in 2021 and recorded in VAERS: 28,330. Eighty percent are harmless (1–2 reports) within the x-axis line; the remaining 20% are more toxic, with the most extreme range up to 5,000 reports. Lesson two asks: “Who did it?” It identifies three companies appearing in VAERS: Moderna, Pfizer, and Janssen (Johnson & Johnson). By filtering VAERS data in Excel, the speaker presents the contributions of each company to the toxic-batch deployment. In the full picture, Moderna accounts for every batch in the first half of the chart except two spikes pre- and post- Moderna, which are attributed to Janssen. Pfizer’s results (from their batches) match the latter half of the chart exactly, suggesting Pfizer appeared to have taken over supply for every USA batch in the latter portion. The deployment is described as carefully compartmentalized, with phases where Janssen, then Moderna, then Janssen again, and then Pfizer dominate in sequence, followed by Moderna exiting and Pfizer continuing. Lesson three describes the purpose behind Moderna’s deployment of toxic batches: Moderna appears to randomly distribute toxic batches, with the intention of harm, possibly to induce fear of a pandemic and justify stronger policies. Janssen’s initial spike is interpreted as a test before Moderna’s deployment. Pfizer is described as carrying out rigorous dosage testing, deploying the most lethal batches systematically and recording effects, and acting as the only company administering batches at that stage to avoid interference from others. Lesson four details the fine art of lethal dosage testing. Pfizer’s deployment is shown as highly clustered in time, forming distinct periods of toxic batches separated by intervals of harmless batches. Toxic batches cluster in discrete ranges (e.g., 3,000–2,500; 2,000–1,500; 1,500–1,000), with abrupt transitions between clusters and harmless periods. Toxicity ranges are not random but follow a stepwise, linear decline across clusters. The speaker concludes that Pfizer deployed highly toxic batches for discrete dosage testing across all states, implying thousands of hospitalizations, injuries, and deaths. The presentation ends by contrasting that 80% of batches are harmless, while a minority exhibit wide toxicity ranges, with claims of systematic, non-random deployment designed for testing, and notes an ironic statement about American exposure to what is described as German-led testing.

The discussion centers on the kill chain concept and Palantir’s role within it. One speaker explains that the system you call the kill chain was created privately, while publicly lawyers frame it as something like “tech for the amelioration of unwanted blah blah blah.” The term kill chain sounds good to him, though not originally Palantir’s; it’s a general military sequence from identifying a target to taking a life. Palantir’s contract added their software and artificial intelligence to the kill chain, making it quicker, and, in his view, “better and more violent.” He notes that stepping back to examine the actual application of these technologies can be destabilizing. Another speaker discusses a personal trajectory: Juan didn’t leave Palantir entirely for ethical reasons, only taking another job, but his motivation to speak out against Palantir grew after observing the Israeli invasion of Gaza following the October 7 attacks. Palantir has contracts with the Israeli Defense Forces, with the exact nature intentionally opaque, yet evidence suggests Palantir’s AI tech was used for target selection in Gaza. The speaker Carp embraces controversy as part of marketing, stating Palantir is comfortable being unpopular. He adds that Palantir works with health insurance companies to build AI for denials management to protect revenue, raising the question of whether Palantir’s AI should decide what care is covered for individuals. A third speaker explains the technical approach: they use what legal scholars call predicate-based search to identify indicators of potential bad behavior in a person’s life. In essence, Palantir makes software that helps customers collect and analyze data and then act on the analysis. By 2013, a decade after founding, Palantir’s client list included the FBI, the CIA, the NSA, the Marines, the Air Force, Special Operations Command, and more. Palantir already had contracts with the IRS to analyze taxpayer data to guide auditors to easier audits, handling financial information for many. They also had multiple contracts with the Department of Health and Human Services, whose core responsibility is Medicare and Medicaid, controlling millions of Americans’ health records and access to health care. A final speaker warns that as we increasingly live in a simulated world, we move toward governance by algorithm, governed by those influencing these AI systems to advance profit- or control-seeking objectives.

I built and implemented a vaccine payment system called pay per dose. While analyzing the data, I noticed discrepancies in the death dates of people who were vaccinated. As the only database administrator for this system in New Zealand, I have access to unique information. I created a chart displaying the top ten batches with high mortality rates. There are a total of 119 batches in New Zealand, mostly Pfizer. To find specific batch information, there is a website called "Find My Batch." I counted the number of vaccinated individuals and identified the deceased within each batch.

Speaker 0: Palantir is described through the Lord of the Rings metaphor, with a logo of a black orb balanced on two leaf-like supports, invoking the mythical Palantirs from Tolkien's work. Palantirs are stones that allowed users to see into the past, future, and other locations, and the logo is used to symbolize Palantir’s mission of using complex data for powerful insights, with a focus on data intelligence and innovation. A Palantir is described as an indestructible crystal ball, and the word is said to come from quinia palan, meaning far or to watch over, which is linked to a surveillance state. The speaker asserts that Palantir has been all over the Trump administration, and claims that Trump has tapped Palantir to compile data on Americans. It is stated that if Palantir teams with Doge, their job becomes easy because Doge has already gained access to the Department of Homeland Security, the Social Security Administration, the IRS, the Department of Health and Human Services, the Department of Housing and Urban Development, the Department of Veterans Affairs, the Department of Personal Management, and the Department of Education. The speaker contends that if they wanted to build a social credit score system, they would have all the information they need. There is a reference to Minority Report, claiming Palantir already has the technology of crime predicting, and that Palantir is now being sold to police departments. The speaker warns that, as in the Minority Report ending, the outcome was not good. The speaker mentions riots in Los Angeles that are planned to spread across the nation, and suggests that an additional biological threat has already been exercised, referencing Event 201. There is a claim that there was a saying about nothing new under the sun, recalling 2020, riots, and stimulus checks. The prediction is that this time there will be universal basic income relief, the rollout of an emergency digital wallet, and soon digital IDs, though they will be labeled differently to sound favorable because of Trump’s tendency to rename things. Palantir is said to take over to ensure universal compliance. The speaker invokes occult language about “order out of chaos,” claiming that people are falling for it. The message asserts that Trump will not save them and reiterates Palantir’s presence since day one. The speaker proclaims that we are living in extraordinary times and asserts that Christians should be excited because of what the Bible says, while those who are scared are described as not in Christ. Finally, there is a call to know Jesus as Lord and Savior, with the Bible verse implication that confessing Jesus as Lord and believing in his death and resurrection will lead to salvation, urging not to wait until it is too late.

"And Trump has been openly building databases on people with Palantir." "Palantir also manages all of your health data Because they contract extensively with HHS." "It was called DEEP and there's been a few arrests under DEEP for people making Facebook posts and things like that." "But anyway, this pitch to that Trump made about having social media spy on its users and use like analytics to, you know, bring about some sort of pre crime society." "didn't ultimately happen in creating this agency called HARPA, which was supposed to be like the health version of the Pentagon's DARPA." "the goal of Palantir, just like it was with total information awareness, is about stopping crime before it happens. It's pre crime." "There's one in LA called Predpol, and they have an accuracy of half a percent."

We built PG, which single handedly stopped, the rise of the far right in in in Europe. We built Foundry, which, was just was used to distribute the COVID vaccine and saved millions of lives globally. We built what we call multi multi constellation and what's often called the digital kill chain, and they're category defining products. So when you deliver these products to the market, just honestly, people say this isn't gonna exist. This isn't valuable, but then it changes the market. And then the market is the Palantir market. Now that doesn't mean everyone in the world's gonna buy our product, but it means most of the sensible people in the world are gonna define buy from the category we defined.

Patrick Sarval is introduced as an author and expert on conspiracies, system architecture, geopolitics, and software systems. Ab Gieterink asks who Patrick Sarval is and what his expertise entails. Sarval describes himself as an IT architect, often a freelance contractor working with various control and cybernetics-oriented systems, with earlier experience including a Bitcoin startup in 2011, photography work for events, and involvement in topics around conspiracy thinking. He notes his books, including Complotcatalogus and Spiegelpaleis, and mentions Seprouter and Niburu in relation to conspiratorial topics. Gieterink references a prior interview about Complotcatalogus and another of Sarval’s books, and sets the stage to discuss Palantir, surveillance, and the internet. The conversation then shifts to explaining Palantir and its significance. Sarval emphasizes Palantir as a key element in a broader trend rather than focusing solely on the company itself. He uses science-fiction analogies to describe how data processing and artificial intelligence are evolving. In particular, he introduces the concept of a “brein” (brain) or “legion” that integrates disparate data streams, builds an ontology, and enables predictive analytics and tactical decision-making. Palantir is described as the intelligence brain that aggregates data from multiple sources to produce meaningful insights. Sarval explains that a rudimentary prototype of such a system operates under the name Lavender in Gaza, where metadata from sources like Meta (Facebook, WhatsApp, Instagram), cell towers, satellites, and other sensors are fed into Palantir. The system performs threat analysis, ranks threats from high to low, and then a military operator—still human—must approve the action, with about 20–25 seconds to decide whether to fire a weapon. The claim is that Palantir-like software functions as the brain behind this process, orchestrating data integration, ontology creation, data fusion, digital twins, profiling, predictions, and tactical dissemination. The discussion covers how Palantir integrates data from medical records, parking fines, phone data, WhatsApp contacts, and more, then applies an overarching data model and digital twin to simulate and project outcomes. This enables targeted marketing alongside military uses, illustrating the broad reach of the platform. Sarval notes there are two divisions within Palantir: Gotum (military) and Foundry (business models), which he mentions to illustrate the dual-use nature of the technology. He warns that the system is designed to close feedback loops, allowing it to learn and refine its outputs over time, similar to how a thermostat adjusts heating based on sensor inputs. A central concern is the risk to the rule of law and human agency. The discussion highlights the potential erosion of the presumption of innocence and due process when decisions increasingly rely on predictive models and AI. The panel considers the possibility that in a high-stress battlefield scenario, soldiers or commanders might defer to the Palantir-presented “world view,” making it harder to refuse an order. There is also concern about the shift toward autonomous weapons and the removal of human oversight in critical decisions, raising fears about the ethics and accountability of such systems. The conversation moves to the political and ideological backdrop surrounding Palantir’s leadership. Peter Thiel, Elon Musk, and a close circle with ties to PayPal and other tech-industry figures are discussed. Sarval characterizes Palantir’s leadership as ideologically defined, with statements about Zionism and a political worldview influencing how the technology is developed and deployed. The dialogue touches on perceived connections to broader geopolitical influence, including the role of influence campaigns, media shaping, and the involvement of powerful networks in technology development and national security. As the discussion progresses, the speakers explore the implications of advanced AI and the “new generative AI” era. They consider the nature of AI and the potential for it to act not just as a data processor but as a decision-maker with emergent properties that challenge human control. The concept of pre-crime—predicting and acting on potential future threats before they materialize—is discussed as a troubling possibility, especially when a machine’s probability-based judgments guide life-and-death actions. Towards the end, the conversation contemplates what a fully dominated surveillance state might look like, including cognitive warfare and personalized influence through media, ads, and social networks. The dialogue returns to questions about how far Palantir and similar systems have penetrated international security programs, with speculation about Gaza, NATO adoption, and commercial uses beyond military applications. The speakers acknowledge the possibility of multiple trajectories and emphasize the need for checks and balances, transparency, and critical reflection on the power such systems confer upon a relatively small group of technologists and influencers. They conclude with a nod to the transformative and potentially dystopian future of AI-enabled surveillance and decision-making, cautioning against unbridled expansion and urging vigilance.

Speaker 0 discusses Whitney Webb's article about HHS Protect and a program called Tiberius provided by Palantir. He claims this is the same Tiberius program believed to be using Gaza to identify drone strike targets, described as the "Homos targets." He states the program was used for Operation Warp Speed to assign people behavior scores, indicating whether they got vaccines, wore masks, or practiced distancing, and that it could reveal location data, ethnicity, finances, and people they have been around. The Tiberius program, he says, would use that information to assign a behavior score. He adds that hospitals sent data such as case mix index and ventilator usage, and that this data was used to target countermeasure strikes—deciding where to send ventilators, remdesivir, and vaccines that people were not taking. He calls this the "Volunteer Tiberias program" and argues that the nefarious aspect is amplified by the existence of drones in America, noting that police in his state and county have had contracts since 2011 to obtain drones and are using them. He mentions a firearms response team acronym, FIT, which would deploy a drone to engage with persons suspected of having firearms instead of sending a police officer, framing it as safer for officers but potentially dangerous for drones. Speaker 0 clarifies whether these are armed or observational drones, speculating they are currently observational. He references a peer-reviewed article about deploying COVID countermeasures with drones delivering packages, including vaccines. He suggests it wouldn’t be hard, noting the military already has LMAMS (low observable munitions or autonomous flying drones) capable of autonomous swarms, which could be used as weapons or to deliver drugs. He closes by tying these points to the possibility of drones playing a role in enforcing countermeasures and distributing medical or military payloads.

HHS is initiating an AI revolution, attracting experts from Silicon Valley to improve government systems. Changes include improving or supplementing the VAERS system using AI. The FDA is using AI to accelerate drug approvals, potentially eliminating the need for primate or animal models. CMS is implementing AI to detect waste, abuse, and fraud. The CDC and other departments will use AI to analyze mega data for better decision-making regarding interventions. AI can assess the effectiveness and side effects of drugs like diabetes medications, statins, and SSRIs across the population. This use of AI has the potential to revolutionize medicine.

Trump has been openly building databases on people with Palantir. Palantir also manages all of your health data Because they contract extensively with HHS. Trump called on social media companies to stop shooters before they commit a crime and to basically flag what people were saying on social media and use that to determine if there should be intervention before a crime might be committed, basically. That's minority report. William Barr, when he was in office the first time, created this program that legalized precrime in The United States, and I think I was, like, one of two people maybe that reported on that at the time. It was called DEEP. The legal framework has been there since, you know, Trump round one. This pitch that Trump made about having social media spy on its users and use like analytics to bring about some sort of pre crime society.

The CDC planned to analyze VAERS data for COVID-19 vaccine safety signals using Proportional Reporting Ratio (PRR), where a score above two would trigger further inquiry. ICANN requested the PRR results via FOIA and found "incredibly concerning results," with some harms having PRRs of 30, 50, or 100. The CDC then switched to Empirical Bayesian (EB) analysis by the FDA. ICANN requested this data via FOIA, leading to two federal lawsuits before the data was released. This data was also "very concerning." Both the PRR analysis and the EB data are available on the ICANN website. The speaker encourages independent scientists to analyze and publish on the data, which confirms "incredibly concerning reports of harm from the COVID-19 vaccine." The speaker claims federal health officials hid this data from the public.

A proper digital infrastructure is critical for managing vaccinations, especially with multiple-shot vaccines. It's essential to track who has been vaccinated. This is important not only for healthcare in general, but specifically for managing pandemics and vaccine distribution. However, most countries currently lack this necessary digital infrastructure.

Speaker 0 discusses The New York Times piece about Trump tapping Palantir to compile data on Americans, noting mixed reactions online and outlining the background. In March, President Trump signed an executive order calling for the federal government to share data across agencies, raising questions about a potential master list of personal information and untold surveillance power. Behind the scenes, officials have quietly placed technological building blocks to enable the plan, with Palantir—the data analysis and technology firm—playing a central role. Palantir is described as more than a data firm. The Trump administration has expanded Palantir’s work across the federal government in recent months. The company has received more than 113,000,000 in federal government spending since Trump took office, including new contracts with the Department of Homeland Security and the Pentagon, plus existing contracts. A separate note mentions a $795,000,000 Department of Defense contract awarded last week that has not yet been spent. Representatives of Palantir are said to be in discussions with at least two other agencies—the Social Security Administration and the Internal Revenue Service—about buying its technology, according to six government officials and Palantir employees. A key Palantir product, Foundry, is used in at least four federal agencies, including DHS and the HHS, widely adopted to organize and analyze data and to pave the way for merging information from different agencies. This is linked to the ability to create detailed portraits of Americans based on government data. Government officials say the administration has sought access to hundreds of data points on citizens and others through government databases, including bank account numbers, student debt amounts, medical claims, and disability status. Critics say such data access could be used to advance political agendas, policing immigrants, and punishing critics; privacy advocates, student unions, and labor rights organizations have filed lawsuits to block data access. A notable point in the piece is that Palantir’s selection as a chief vendor was driven by Elon Musk’s Department of Government Efficiency, with at least three Doge members formerly at Palantir and two others who had worked at Peter Thiel-funded companies. Some current and former Palantir employees have expressed unease, with 13 former employees signing a letter urging Palantir to stop its endeavors with President Trump, including Linda Shah, a Palantir engineer who left last year, who said the concern was not the technology but how the administration planned to use it. The article also notes Palantir’s main products: Foundry and Gotham, the latter described as helping organize and draw conclusions from data and tailored for security and defense purposes. Gotham is interpreted by some as precrime software. Palantir was founded with initial funding from the CIA’s venture capital arm, In-Q-Tel, and Peter Thiel’s Founders Fund, and In-Q-Tel also funded Founders Fund. Speaker 1 interjects with a quote from Palantir’s Alex Karp claiming Palantir built PG to stop the rise of the far right in Europe and to distribute the COVID vaccine with Foundry, and to create a “digital kill chain.” Speaker 0 questions the desirability of a technology that compiles banking data, social security information, online presence, and other personal data for precrime analysis across government, especially under an administration associated with claims of stopping a far-right rise. The discussion continues with concerns about the potential weaponization of data and the implications for speech, political ideology, and dissent.

HHS Protect, started during Operation Warp Speed, used two Palantir programs. While documentation suggests planning began over a decade prior with Operation Stargate and CAIA databases, HHS Protect involved the AMA, HHS, and CDC partnering with Palantir. Palantir developed a program for Operation Warp Speed that assigned people a threat risk score via a program called Tiberius. AI databases from companies like Palantir, 3M, and Epic share information. Tiberius assessed compliance with lockdown measures, vaccination status, and masking, determining individual and ZIP code-level compliance. According to Whitney Webb, HHS Protect targeted ethnic groups, incorporating ethnicity into the threat risk score. Gotham, Palantir's AI kill chain program, used the threat risk score from Tiberius to decide when and where to deploy countermeasures like vaccines, Remdesivir, and ventilators. HHS Protect monitored this process, identifying hospitals and patients based on algorithms to execute interventions using the Gotham program.

I'm just gonna give you a punch list of some of the clandestine things the WHO has been doing behind closed doors on the pandemic treaty front, but on the sort of global convergence of, you know, emergency crisis response. But what they don't tell you is that emergency means climate change or racial inequity. Take your pick of woke buzzword. But they created the public health and social measures decision navigator, The two point o platform, which will quote, identify relevant content from websites, social media, and other public sources to identify important health events. It's called the epidemic intelligence from open sources, and essentially, they launched a new AI pandemic tracker that's going to be monitoring and essentially patrolling social media to see what kind of misinformation they need to crack down on their fusing essentially new AI tools, to be able to do this so they can process more sources, get probably more of your social media posts, more of the war room clips, that you share. They've also announced progress. This is another story of mine on what they call the pathogen access and benefit sharing system. They have a nice little acronym for it, the PABSS system, where they this one's actually quite wild. They're working on a pandemic causing pathogen database global sharing initiative. Yes. You heard that right. They didn't learn anything from COVID, or I guess maybe they learned everything if what they cared to learn was how to cause a global pandemic. They're pretty good at that. But they are providing quotes, catch this, safe, transparent, and accountable access to pathogens with pandemic potential to all WHO member states, not just China, but every country. They also want to guarantee, quote, equitable, rapid, and timely sharing of countermeasures buried there. What they don't tell you, they mean vaccines. And they also want to, quote, strengthen global health preparedness by pooling resources across borders, which as you and I both know, that is just a dog whistle for suppressing not just nationalism, but the idea of hypernational supply chains and not being reliant on what we saw. It was the completely defunct and completely inadequate globalized supply chains that failed, that are, of course, reliant on probably the UN, WHO's largest benefactor, China, but totally failed during COVID. That's just some of the latest things that the WHO is working on. It's absolutely wild. And I think it goes back to sort of the key point that Nora was making. And even you see with the Bolton stuff, right, Even when we come after these people and rightfully so, they are not just sitting and cowering. They are rebranding. They are like a hydra. They are coming back with even greater force because they know they are lashing out in their last few breaths, again, metaphorically, but seeking because they understand, right, that this is a a serious existential threat.

So there was a program called HHS Protect as start during operation warp speed. So this HHS protect program is really interesting because what it did, it used two different Palantir programs. The AMA, HHS, the CDC, specifically, all partnered with Palantir, and then Palantir developed a program for operation warp speed. And that program, what it did was it assigned people a threat risk score, and then that was a program called Tiberius. They also could determine down to the ZIP code where you were and how compliant areas were. And then Gotham is the AI kill chain program created by Palantir. So the Gotham program, it takes the threat risk score from Tiberius, and then it executes the threat or tells does an AI decision making process and decide decides when and how and where to deploy the countermeasures, which was your vaccine, your remdesivir, and your ventilator.

Total Information Awareness (TIA) was defunded by Congress not long after it launched because mainstream media and organizations like the ACLU said it would end privacy for Americans and was unconstitutional. It was described as something that would spy on all Americans and decide who would commit a crime before it happened, including terror attacks and bioterror, and even pandemics before they happen. The policies behind TIA resurfaced during the Trump administration during COVID, with Palantir as the contractor for those efforts. TIA originated related to MAINCORE. The claim is that they would use every telephone call, every text, every Google search, and every website visited, collecting all of that data and putting it into a database on an individual. After the invention, organizations pushed back, and the government said they wouldn’t pursue it anymore. Palantir then stepped in, arguing they could do it, even though Palantir did not exist yet at that time. It is claimed that Palantir was created by Peter Thiel as TIA faced public backlash, and that in the setup they used Richard Pearl to connect with Poindexter, who was running TIA, to privatize the program and have Palantir do what TIA had intended to do. TIA, although housed in DARPA, was intimately pushed and developed with CIA involvement, specifically by the CIA’s chief information officer at the time, Alan Wade, who is described as a business partner of Ghislain Maxwell’s sister Christine. A broader scope is highlighted to show the ominousness of these efforts, noting that Poindexter and a DARPA program manager were involved in LifeLog, a project seeking to build a database tracking a person’s entire existence. LifeLog aimed to collect an individual’s relationships and communications (phone calls, mail, email), plus media consumption, purchases, and more to build a digital record of everything a person says, sees, or does. LifeLog would then take unstructured data and organize it into discrete episodes or snapshots while mapping relationships, memories, events, and experiences. This context is tied to Peter Thiel’s current influence, with Thiel described as the person pushing these private-sector efforts and now being responsible for J. D. Vance’s funding and for connecting J. D. Vance with Donald Trump, including funding of Vance’s campaign. The discussion concludes with the claim that Palantir is really a CIA front.

In 2012, DARPA initiated the ADEPT Protect P3 program for pandemic prevention using gene-encoded vaccines. The military had been working on mRNA vaccines since then, not just in response to COVID-19. The rapid development of vaccines under Operation Warp Speed was part of a long-term military program. The FDA's lack of control over the process is due to its military origins. The military approach to vaccine development leaves no one exempt.

Speaker 0 discusses the origin and framing of pandemic prevention and vaccine development as a military-led initiative. He cites a 2012 DARPA program called the Adept Protect p three program, described as a pandemic prevention platform. The proposal outlined the use of gene-encoded vaccines based on RNA or DNA with the goal of stopping a pandemic within sixty days. He suggests that, by the time President Trump referenced “Operation Warp Speed” to develop vaccines, there should have been preparation and acknowledgement that this work dated back to 2012, making it not rapid innovation but a decade-long effort. He argues that the public narrative of rapid development and stunning innovation surrounding vaccines is deceptive and that contractors like Moderna had already secured multi-million-dollar contracts in 2013. He notes that the military operates programs addressing biological threats and also works on answers such as monoclonal antibodies and vaccines. The claim is made that the military originated the idea of messenger RNA vaccines, not Pfizer or Moderna, and not in response to the outbreak from Wuhan. According to the speaker, this is a military program in origin and administration. The speaker asserts that Health and Human Services, under Alex Azar, together with the Department of Defense, ushered the public into a vaccine era, framing Emergency Use Authorization as a mechanism to rapidly deploy new technology into the military rather than the public. He contends that this mechanism’s broad public application began with the COVID-19 pandemic, which is presented as evidence that the FDA lacks ownership or control over the process because the program is characterized as military in origin and execution. The overall claim is that the program operates like a military operation with universal reach and without exemptions, implying a deeply embedded military approach to vaccine development and deployment. Throughout, the speaker emphasizes the continuity from a 2012 program proposal through to the public health landscape observed during and after the COVID-19 pandemic, asserting that the military’s involvement, timeline, and governance underlie the current vaccine paradigm and its regulatory pathways.