• A new prediction on the Singularity…
  • Can AI reduce our health care expenses?
  • Do-it-yourself genetic engineering?

Dear Reader,

They’re now calling it “directed evolution.”

Last week, on Wednesday night, an independent journalist released a video on Twitter that has now been viewed more than 25 million times. It’s the kind of video that would have been immediately censored had Elon Musk not taken over Twitter and restored freedom of speech and freedom of the press.

It’s a video of Jordan Trishton Walker, the Director of Research and Development for Strategic Operations and mRNA Scientific Planning at none other than Pfizer. The video says it all. We can watch it directly from the source right here. But fair warning, what the Pfizer exec says, and how he says it, is deeply disturbing.

Walker’s employment has been verified, and the video is real. One U.S. senator has already sent a letter to the CEO of Pfizer demanding answers, and other members of Congress are now asking for hearings.

What’s all the fuss about? Here are a few things that Walker said on the video:

Well one of the things we’re exploring is like, why don’t we just mutate it (the virus) ourselves so we could – we could create preemptively develop new vaccines, right? So, we have to do that. If we’re gonna do that though, there’s a risk of life, as you could imagine, no one wants to be having a pharma company mutating f**king viruses.

When talking about gain of function research:

Directed evolution is very different. Well you’re not supposed to do Gain-of-Function research with the viruses. They’d rather we not, but we do these selected structure mutations to try to see if we can make them more potent. So there is research ongoing about that.

The way it would work is like we put them in – the virus in these monkeys. And then we successively, like, cause them to keep infecting each other. And we collect serial samples from them, and then, the ones that are more infectious, to like, the virus we’ll put them in another monkey and you just constantly actively mutate it.

You can now force it (the virus) to mutate in a certain way you want it.

Well, they are still kind of conducting the experiments on it, but it seems like, from what I’ve heard, they’re kind of optimizing it. But they’re going slow cause everyone’s very cautious, like, you know, obviously they don’t want to accelerate it too much, but I think they’re also just trying to do it as an exploratory thing because you obviously don’t want to advertise that you are figuring out future mutations.

When talking about Pfizer:

It (Pfizer) is a revolving door for all government officials. It’s pretty good for the industry to be honest. It’s bad for everyone else in America.

Either way, it’s going to be a cash cow. COVID will probably be a cash cow for us for a while going forward.

The words speak for themselves. But for those of us that watch the video, what stands out the most is sheer hubris… the loose, whimsical, and excited way in which Walker speaks out Pfizer’s secretive work on mutating the COVID virus.

Since gain of function research, which is what was conducted in Wuhan with funding by Fauci and the NIH, is considered “bad” now, they’ll just call it something else – “directed evolution.” I can imagine the internal discussions… They’re just directing the evolution of the virus… Just giving it a nudge in the right direction to become more potent or viral.

The release of the video created so much noise, Pfizer was forced to make a statement. It was remarkably general, concerning “Allegations have been recently made related to gain of function and directed evolution research.”

Pfizer denies conducting either in a direct contradiction to Walker’s recorded comments. Yet in the same press release admits to doing so when it says, “In a limited number of cases when a full virus does not contain any known gain of function mutations, such virus may be engineered to enable the assessment of antiviral activity in cells.”

To most of us, learning of something like this probably comes as no surprise. Tens of billions of dollars of profit has been made already, billionaires have been minted, and it doesn’t take much extrapolation to realize that there are many who want to keep the gravy train rolling.

Between the government agencies and the pharmaceutical companies involved, we’ve been played.

We’re all being played.

The Singularity is just seven years away?

A tech firm that’s working in the artificial intelligence (AI) space just published some research about when it believes we will reach the Singularity.

The concept of the Singularity was made famous by Ray Kurzweil’s 2005 book titled The Singularity is Near.

The term refers to the point in time where technological advancement becomes so fast that it’s gone out of control. There’s no way humans can keep up with it. And a big part of this dynamic is that AIs start working and creating intelligently even when they aren’t asked to do so.

This is something that’s long been theorized about in the realm of science fiction. But this latest forecast has put a specific time frame on it based on the advancements that it is seeing in its sector of artificial intelligence.

The researchers made this projection based on a rather simple metric that they’ve been tracking since 2014. It’s called “Time to Edit” (TTE). It calculates the time it takes for professional human editors to fix AI-generated language translations.

So TTE basically measures how accurate AI-based language translations are. The more accurate, the less time it takes a human to fix them.

Based on their work with TTE, these researchers project that we’ll reach the Singularity as soon as 2030. We’re just seven years away.

Here’s the chart they used to make this projection:

Source: Translated

Here we can see a very clear trend.

When this research started in 2014, it took humans an average of almost four seconds per word to correct AI translations. By 2022 that number was down to just two seconds.

And we can see the researchers are extrapolating this trend out over the next several years. The current trajectory suggests TTE will hit one second around 2030 or even sooner. That’s when AI translations will be perfect and will not need any corrections.

To be clear, the framework for the prediction is fairly simple and only incorporates one application of AI. But sometimes simple models can be quite useful benchmarks.

And for the record, I think this projection is a good one.

Personally, I went on record back in 2019 and predicted that we would see artificial general intelligence (AGI) by 2028.

If we remember, AGI is the point at which an AI can perform general tasks as well or better than humans in just about any discipline we can imagine. It’s where AIs can become experts in any field.

The Singularity is just one step further than that. And it’s logical to expect AGI to accelerate our path to the Singularity.

So if I’m right about AGI by 2028, it’s not at all a stretch to think that we’ll hit the Singularity just a few years later.

The bottom line here is that this isn’t something that’s decades away. We’re likely less than ten years away from technological advancement getting out of control. And that will change everything about our society.

I’ve said before that one of the greatest challenges of our generation will be to manage through this incredible disruption, and to employ an ethical and safe framework for the use of this powerful technology. And of course, society will also have to defend against those who desire to use it for nefarious purposes. And yes, it will require another AI to defend against systems that use artificial intelligence.

We’re on the cusp of entering a golden age, and it is going to require extraordinary efforts and restraint to avoid a disastrous outcome.

AI has the potential to make health insurance cost less…

While the Singularity and AGI may be somewhat scary to think about, it’s important to point out that AI will bring with it some incredible developments between now and then.

Case in point – a group of Harvard researchers just put out an exciting report around AI and healthcare. Specifically, the research team calculated how much money AI will be able to save us in healthcare costs going forward.

To set the stage, healthcare costs are typically one of the biggest expenses for people in developed countries. For instance, in the United States, it’s estimated that the average person spent just over $10,000 on healthcare expenditures in 2020. And these costs tend to go up each year. This leads to health insurance costs going up every year as well.

But what would happen if AI were widely deployed throughout the healthcare industry? That’s what these researchers set out to answer.

And their findings are incredible. This research projects that AI could reduce healthcare spending by five to 10 percent per year. That equates to annual savings between $200—300 billion.

These cost savings come from optimizing and automating healthcare operations where possible. In addition, AI will help us proactively identify potential adverse events so we can act to mitigate or avoid them entirely. It’s much cheaper and easier to take preventative measures than it is to treat health problems after they set on.

What’s more, AI will be able to determine exactly which therapies are ideal for every patient based on their individual genetic makeup. This will lead to less trial and error and better overall health outcomes for everybody.

In summary, AI can be used to drive health care spending down while improving overall health. That, in turn, will lead to declining health insurance costs.

This is a great data point, and it also vindicates one of our major investment trends: precision medicine.

As longtime subscribers of my research know, the intersection of advanced technology like artificial intelligence and healthcare will present some of the best investing opportunities over the next decade. And our model portfolio is chalk full of these companies.

Out of respect to our paid readers, I won’t name the companies here. But subscribers to Exponential Tech Investor can catch up on one of my favorite companies in this space right here. This company is “unleashing” artificial intelligence on the process of drug discovery. It’ll be a beneficiary as this larger trend plays out.

And if any subscribers would like to join us, please feel free to learn more here.

Would you CRISPR yourself…?

An interesting trend has emerged in the genetic editing space. Do-it-yourself genetic engineering kits are now widely available.

I know this may sound concerning. Should people really be able to experiment with genetic editing at home?

Well, I’ve long maintained that genetic editing is almost like working with software code. It can cut DNA and replace mutations with corrected segments. And this can be done just by a single person.

A company has sprung up to provide both at-home genetic editing kits and educational how-to videos. Here’s a look at some of the available kits:

Source: Odin

What’s interesting here is that there’s a variety of at-home kits available.

The cheapest is a genetic engineering kit for plants. It costs between $150 and $199. Then there’s a Bioengineering 101 kit that costs between $200 and $379. And for those who want to go all the way, there’s the complete genetic engineer home lab kit for $1,549.

Again, these kits come with all the lab tools as well as the educational content that explains how to use them.

It’s amazing to think about – advanced life sciences research has always been accessible exclusively to corporations and governments. That’s because it required expensive laboratories with high operational costs.

Not anymore.

In the world of genetic editing, tests and edits can be done just by a single person in their garage or basement. And with the right tools and information, no prior experience is required. Remarkable.

Obviously this could lead to some really bad outcomes. And I’d like to avoid any misunderstandings… I definitely do not recommend anyone use these at home kits to genetically engineer themselves.

But given how inexpensive the “tools” are for genetic engineering, I guarantee we’ll see some clever inventors come up with some major breakthroughs. And for those motivated and interested students, hands on learning like this with something like a plant could inspire the next generation of scientists.

This is part of a massive trend democratizing access to high tech. Whether it is working with artificial intelligence, computer vision, additive manufacturing, or genetic engineering, these are now accessible to just about anyone.

These technologies are no longer the domain of large corporations and the government, which means individuals are empowered to create and invent even more than what has been possible in the past.


Jeff Brown
Editor, The Bleeding Edge