While AI is incredible and has many usages, it is so confusing and produces so much "slop" (bad quality outputs) because of lack of proper education among the population that instead of me being without a job, people ask me if the AI is right on its takes.
In tech (or even biotech i this instance) GIGO still means "garbage in = garbage out". 😑
Just as the same issue exists in ALL technocratic science at the moment and looking ahead into the future- its a PEBCAP problem😐 = "Problem Exists Between Chair and PC", being the person inputting the data. $#!@ algorithms are still $#!@ whether done by AI or not, because AI is only using data acquired by the clever idiot that programmed the algorithms, even the LLMs. They cant "learn" on $#!@, and unfortunately or actually BECAUSE of our tech, WE have been getting stupider, not smarter.😐🤦♀️🤦♀️
GeneOptimizer (Raab sliding window algo) is more deterministic, avoids dataset biases, it more efficient when you use vast sequences, is more accurate in codon stability and immunogenicity, and balanced GC content to prevent misfolding (probably why the proline was added, and where), motif elimination (TLR-activating CpG sequences ones). Also more "scale friendly).
They would need a highly sophisticated epitope prediction tool and experimental validation to avoid the downsides, which you and I both know they skipped that part lol.
I'm thinking that, in spite of the medical freedom groups going on a freak out/betrayal-baying- at-the-moon rant, this AI is for mostly surveillance. What do you think? What advantage is there to have these huge AI facilities? How can it help us in day to day living? If it could stop child trafficking and do away with all the crooks, I'd be all in, but so far I am not aware of personal benefit.
Just in -- Trump admin supposedly working on executive order halt to federal funding of GOF.
Surveillance was overly present and abundant before AI, AI will just enable the analysis of all the data faster, and new ways to surveil of course, but mostly it is an architecture problem.
Current Machine Learning and AI architecture is AWFULLY INNEFICIENT. We are, quite literally, brute forcing our way out of problems, scalding up more and more because there are not enough algorithmic and architectural breakthroughs. Widespread use of AI, and especially nation-state level usage will require massive data centers under current conditions.
GoF will be exported to allied countries as it has been done for the last decades, it will avoid oversight, no stopping it in the age of AI too.
As venoms and toxins are being used in medicines (Gila Monster venom weight loss, snake venom blood thinners, cone snail venom opioid pain substitute, etc.), 🌽sider the similarities between the Ordeal Bean and the mRNA myocarditis clot shots. Calabar Ordeal Beans were given to prisoners to ascertain guilt or innocence in witch hunt drowning style. It the prisoners died, they were guilty. And the poison was a slow acting heart attack. Those who survived the bioweapons in Cov19 and the biosynth modified mRNA were “innocent” of weaker genes for TransHumanist Eugenics trying to Cull the Herd of weaker guilty genes. Dying straight off. Or a more slow acting myocarditis poisoned “died suddenly” death.
I've bookmarked this for future reference. Thank you, it's going to be super helpful to me. I'll look into getting your book when it's published! The work effort is astounding so I wish you great future success!
How will AI help them avoid the mistakes of last time in terms of LNP proliferation, cDNA creation, deposition of spike in endothelial cells, heart, testes, ovaries etc.?
They have no data at physiological level to model dynamics, so how will any models save them?
They had an opportunity where they could have allowed autopsies, which would have been equivalent of a time series as people dropped at different points in the journey of the spike in the bloodstream. But they blocked that.
So they don't have direct data.
The VAERS and the other app that they canned have indirect data, so they have to mine that first, set up hypotheses, and then simulate them in software. Even if they reproduce symptoms it does not mean they have the actual cause. How many years will this take even for the pharma industry?
On top of this, deep learning models need huge amounts of data.
Now, overlay the tech bros who have no idea what they are getting into. How many decades will that take?
Even if these bros are just pipes, why would they expect pharma to have not started their AI infrastructure already? From what you mention, they are ahead of these people.
Your first question. The deep learning mRNA distribution paper. They now can do it at a single cell level,
And I remember, clear as day both Pfizer and Moderna CEO proudly announcing they would be able to track each vaccine in each arm.
I have argued since 2022, they have excessive amounts of data and had no way to use it. Biotech has enough data to schedule all data centers in the US for dozens of years.
The project sounds desperate play from OpenAI hehe.
Moriarty, there is a different explanation that works. Assume the "story" about these companies creating the vaxxxines so quickly is what they decided to say to cover that they actually got the procedural cookbook from the bio-labs in Ukraine that were not only developing the C19 virus and its spike but also the vaxxxine design and production process. Given that C19 itself was Part 1 of a binary bioweapon-in-time, those wanting to spread that thing would want it to be the excuse to push a much more serious Part 2 bioweapon-in-time vaxxxine. They would have developed both as a tailored set. So your argument that the Pharma AIs chose the spike protein because of the RBD would be replaced by the idea that the bio-lab folks deliberately *chose* the spike protein because they wanted the maiming and the deaths. They then gave that idea and the necessary production process to Big Pharma to scale up (which they did poorly, but the GoF folks releasing C19 would have seen the contamination as a bonus, probably). In any case, I'm sure the Pharma companies involved did have AI software, but I am contending the original data came from the bio-labs along with the design of the vaxxxine to be made and the way to make it. Your approach assumes stupidity on the part of Pharma. My approach assumes malice on the part of those who designed and released C19 *and* stupidity and greed on the part of the Pharma companies. Too many things about C19 et al go in the wrong direction not to assume malice on *someone's* part. The press conference with Trump, Ellison, Son, and Altman was classic Trump-putting-bad-people-into-the-public-eye. Elon said later on X "They don't have the money." He despises Altman (perhaps rightfully). Ellison's hotel on Lake Tahoe just closed to events for some reason, and Son has been playing games for a long time and somehow staying afloat. Once someone online pointed out the body language, I started laughing.
While AI is incredible and has many usages, it is so confusing and produces so much "slop" (bad quality outputs) because of lack of proper education among the population that instead of me being without a job, people ask me if the AI is right on its takes.
Lol, lmao even, I got that one wrong.
In tech (or even biotech i this instance) GIGO still means "garbage in = garbage out". 😑
Just as the same issue exists in ALL technocratic science at the moment and looking ahead into the future- its a PEBCAP problem😐 = "Problem Exists Between Chair and PC", being the person inputting the data. $#!@ algorithms are still $#!@ whether done by AI or not, because AI is only using data acquired by the clever idiot that programmed the algorithms, even the LLMs. They cant "learn" on $#!@, and unfortunately or actually BECAUSE of our tech, WE have been getting stupider, not smarter.😐🤦♀️🤦♀️
#bluelightbrains #follownone #mistakeswereNOTmade #getlocalised
As for Pfizer using AI to design and codon-optimize BNT162b2, there were 2 versions admitted to (maybe there were versions 1-7?)
version 8 which used a BioNTech proprietary algorithm
version 9 which used a published algorithm (Raab et al. 2010)
they decided on version 9.....I have always wondered why
GeneOptimizer (Raab sliding window algo) is more deterministic, avoids dataset biases, it more efficient when you use vast sequences, is more accurate in codon stability and immunogenicity, and balanced GC content to prevent misfolding (probably why the proline was added, and where), motif elimination (TLR-activating CpG sequences ones). Also more "scale friendly).
They would need a highly sophisticated epitope prediction tool and experimental validation to avoid the downsides, which you and I both know they skipped that part lol.
Thanks for that explanation! I just thought it was ironic that a published algorithm worked better than their proprietary one. As for the rest…..yeah.
I'm thinking that, in spite of the medical freedom groups going on a freak out/betrayal-baying- at-the-moon rant, this AI is for mostly surveillance. What do you think? What advantage is there to have these huge AI facilities? How can it help us in day to day living? If it could stop child trafficking and do away with all the crooks, I'd be all in, but so far I am not aware of personal benefit.
Just in -- Trump admin supposedly working on executive order halt to federal funding of GOF.
Surveillance was overly present and abundant before AI, AI will just enable the analysis of all the data faster, and new ways to surveil of course, but mostly it is an architecture problem.
Current Machine Learning and AI architecture is AWFULLY INNEFICIENT. We are, quite literally, brute forcing our way out of problems, scalding up more and more because there are not enough algorithmic and architectural breakthroughs. Widespread use of AI, and especially nation-state level usage will require massive data centers under current conditions.
GoF will be exported to allied countries as it has been done for the last decades, it will avoid oversight, no stopping it in the age of AI too.
As venoms and toxins are being used in medicines (Gila Monster venom weight loss, snake venom blood thinners, cone snail venom opioid pain substitute, etc.), 🌽sider the similarities between the Ordeal Bean and the mRNA myocarditis clot shots. Calabar Ordeal Beans were given to prisoners to ascertain guilt or innocence in witch hunt drowning style. It the prisoners died, they were guilty. And the poison was a slow acting heart attack. Those who survived the bioweapons in Cov19 and the biosynth modified mRNA were “innocent” of weaker genes for TransHumanist Eugenics trying to Cull the Herd of weaker guilty genes. Dying straight off. Or a more slow acting myocarditis poisoned “died suddenly” death.
https://naturespoisons.com/2014/04/15/physostigmine-from-ordeal-poison-to-valuable-medicine-calabar-bean/
I've bookmarked this for future reference. Thank you, it's going to be super helpful to me. I'll look into getting your book when it's published! The work effort is astounding so I wish you great future success!
👍👍👍
Pfizer alone using AI? Rather some kind of teamwork: https://www.arkmedic.info/p/how-many-coincidences
'personalized medicine' in a form of SYNTHETIC GENETIC materials is called GENE THERAPY. It overwrites your ORIGINAL HUMAN GENOME.
Why don't you finally change your language in order to really help UNEDUCATED people to completely reject that lethal, lifeless technology???
How will AI help them avoid the mistakes of last time in terms of LNP proliferation, cDNA creation, deposition of spike in endothelial cells, heart, testes, ovaries etc.?
They have no data at physiological level to model dynamics, so how will any models save them?
They had an opportunity where they could have allowed autopsies, which would have been equivalent of a time series as people dropped at different points in the journey of the spike in the bloodstream. But they blocked that.
So they don't have direct data.
The VAERS and the other app that they canned have indirect data, so they have to mine that first, set up hypotheses, and then simulate them in software. Even if they reproduce symptoms it does not mean they have the actual cause. How many years will this take even for the pharma industry?
On top of this, deep learning models need huge amounts of data.
Now, overlay the tech bros who have no idea what they are getting into. How many decades will that take?
Even if these bros are just pipes, why would they expect pharma to have not started their AI infrastructure already? From what you mention, they are ahead of these people.
This entire project sounds not well thoughtout.
Your first question. The deep learning mRNA distribution paper. They now can do it at a single cell level,
And I remember, clear as day both Pfizer and Moderna CEO proudly announcing they would be able to track each vaccine in each arm.
I have argued since 2022, they have excessive amounts of data and had no way to use it. Biotech has enough data to schedule all data centers in the US for dozens of years.
The project sounds desperate play from OpenAI hehe.
Moriarty, there is a different explanation that works. Assume the "story" about these companies creating the vaxxxines so quickly is what they decided to say to cover that they actually got the procedural cookbook from the bio-labs in Ukraine that were not only developing the C19 virus and its spike but also the vaxxxine design and production process. Given that C19 itself was Part 1 of a binary bioweapon-in-time, those wanting to spread that thing would want it to be the excuse to push a much more serious Part 2 bioweapon-in-time vaxxxine. They would have developed both as a tailored set. So your argument that the Pharma AIs chose the spike protein because of the RBD would be replaced by the idea that the bio-lab folks deliberately *chose* the spike protein because they wanted the maiming and the deaths. They then gave that idea and the necessary production process to Big Pharma to scale up (which they did poorly, but the GoF folks releasing C19 would have seen the contamination as a bonus, probably). In any case, I'm sure the Pharma companies involved did have AI software, but I am contending the original data came from the bio-labs along with the design of the vaxxxine to be made and the way to make it. Your approach assumes stupidity on the part of Pharma. My approach assumes malice on the part of those who designed and released C19 *and* stupidity and greed on the part of the Pharma companies. Too many things about C19 et al go in the wrong direction not to assume malice on *someone's* part. The press conference with Trump, Ellison, Son, and Altman was classic Trump-putting-bad-people-into-the-public-eye. Elon said later on X "They don't have the money." He despises Altman (perhaps rightfully). Ellison's hotel on Lake Tahoe just closed to events for some reason, and Son has been playing games for a long time and somehow staying afloat. Once someone online pointed out the body language, I started laughing.