Tag Archives: Industry

#437345 Moore’s Law Lives: Intel Says Chips ...

If you weren’t already convinced the digital world is taking over, you probably are now.

To keep the economy on life support as people stay home to stem the viral tide, we’ve been forced to digitize interactions at scale (for better and worse). Work, school, events, shopping, food, politics. The companies at the center of the digital universe are now powerhouses of the modern era—worth trillions and nearly impossible to avoid in daily life.

Six decades ago, this world didn’t exist.

A humble microchip in the early 1960s would have boasted a handful of transistors. Now, your laptop or smartphone runs on a chip with billions of transistors. As first described by Moore’s Law, this is possible because the number of transistors on a chip doubled with extreme predictability every two years for decades.

But now progress is faltering as the size of transistors approaches physical limits, and the money and time it takes to squeeze a few more onto a chip are growing. There’ve been many predictions that Moore’s Law is, finally, ending. But, perhaps also predictably, the company whose founder coined Moore’s Law begs to differ.

In a keynote presentation at this year’s Hot Chips conference, Intel’s chief architect, Raja Koduri, laid out a roadmap to increase transistor density—that is, the number of transistors you can fit on a chip—by a factor of 50.

“We firmly believe there is a lot more transistor density to come,” Koduri said. “The vision will play out over time—maybe a decade or more—but it will play out.”

Why the optimism?

Calling the end of Moore’s Law is a bit of a tradition. As Peter Lee, vice president at Microsoft Research, quipped to The Economist a few years ago, “The number of people predicting the death of Moore’s Law doubles every two years.” To date, prophets of doom have been premature, and though the pace is slowing, the industry continues to dodge death with creative engineering.

Koduri believes the trend will continue this decade and outlined the upcoming chip innovations Intel thinks can drive more gains in computing power.

Keeping It Traditional
First, engineers can further shrink today’s transistors. Fin field effect transistors (or FinFET) first hit the scene in the 2010s and have since pushed chip features past 14 and 10 nanometers (or nodes, as such size checkpoints are called). Korduri said FinFET will again triple chip density before it’s exhausted.

The Next Generation
FinFET will hand the torch off to nanowire transistors (also known as gate-all-around transistors).

Here’s how they’ll work. A transistor is made up of three basic components: the source, where current is introduced, the gate and channel, where current selectively flows, and the drain. The gate is like a light switch. It controls how much current flows through the channel. A transistor is “on” when the gate allows current to flow, and it’s off when no current flows. The smaller transistors get, the harder it is to control that current.

FinFET maintained fine control of current by surrounding the channel with a gate on three sides. Nanowire designs kick that up a notch by surrounding the channel with a gate on four sides (hence, gate-all-around). They’ve been in the works for years and are expected around 2025. Koduri said first-generation nanowire transistors will be followed by stacked nanowire transistors, and together, they’ll quadruple transistor density.

Building Up
Growing transistor density won’t only be about shrinking transistors, but also going 3D.

This is akin to how skyscrapers increase a city’s population density by adding more usable space on the same patch of land. Along those lines, Intel recently launched its Foveros chip design. Instead of laying a chip’s various “neighborhoods” next to each other in a 2D silicon sprawl, they’ve stacked them on top of each other like a layer cake. Chip stacking isn’t entirely new, but it’s advancing and being applied to general purpose CPUs, like the chips in your phone and laptop.

Koduri said 3D chip stacking will quadruple transistor density.

A Self-Fulfilling Prophecy
The technologies Koduri outlines are an evolution of the same general technology in use today. That is, we don’t need quantum computing or nanotube transistors to augment or replace silicon chips yet. Rather, as it’s done many times over the years, the chip industry will get creative with the design of its core product to realize gains for another decade.

Last year, veteran chip engineer Jim Keller, who at the time was Intel’s head of silicon engineering but has since left the company, told MIT Technology Review there are over a 100 variables driving Moore’s Law (including 3D architectures and new transistor designs). From the standpoint of pure performance, it’s also about how efficiently software uses all those transistors. Keller suggested that with some clever software tweaks “we could get chips that are a hundred times faster in 10 years.”

But whether Intel’s vision pans out as planned is far from certain.

Intel’s faced challenges recently, taking five years instead of two to move its chips from 14 nanometers to 10 nanometers. After a delay of six months for its 7-nanometer chips, it’s now a year behind schedule and lagging other makers who already offer 7-nanometer chips. This is a key point. Yes, chipmakers continue making progress, but it’s getting harder, more expensive, and timelines are stretching.

The question isn’t if Intel and competitors can cram more transistors onto a chip—which, Intel rival TSMC agrees is clearly possible—it’s how long will it take and at what cost?

That said, demand for more computing power isn’t going anywhere.

Amazon, Microsoft, Alphabet, Apple, and Facebook now make up a whopping 20 percent of the stock market’s total value. By that metric, tech is the most dominant industry in at least 70 years. And new technologies—from artificial intelligence and virtual reality to a proliferation of Internet of Things devices and self-driving cars—will demand better chips.

There’s ample motivation to push computing to its bitter limits and beyond. As is often said, Moore’s Law is a self-fulfilling prophecy, and likely whatever comes after it will be too.

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Posted in Human Robots

#437267 This Week’s Awesome Tech Stories From ...

ARTIFICIAL INTELLIGENCE
OpenAI’s New Language Generator GPT-3 Is Shockingly Good—and Completely Mindless
Will Douglas Heaven | MIT Technology Review
“‘Playing with GPT-3 feels like seeing the future,’ Arram Sabeti, a San Francisco–based developer and artist, tweeted last week. That pretty much sums up the response on social media in the last few days to OpenAI’s latest language-generating AI.”

ROBOTICS
The Star of This $70 Million Sci-Fi Film Is a Robot
Sarah Bahr | The New York Times
“Erica was created by Hiroshi Ishiguro, a roboticist at Osaka University in Japan, to be ‘the most beautiful woman in the world’—he modeled her after images of Miss Universe pageant finalists—and the most humanlike robot in existence. But she’s more than just a pretty face: Though ‘b’ is still in preproduction, when she makes her debut, producers believe it will be the first time a film has relied on a fully autonomous artificially intelligent actor.”

VIRTUAL REALITY
My Glitchy, Glorious Day at a Conference for Virtual Beings
Emma Grey Ellis | Wired
“Spectators spent much of the time debating who was real and who was fake. …[Lars Buttler’s] eyes seemed awake and alive in a way that the faces of the other participants in the Zoom call—venture capitalist, a tech founder, and an activist, all of them puppeted by artificial intelligence—were not. ‘Pretty sure Lars is human,’ a (real-person) spectator typed in the in-meeting chat room. ‘I’m starting to think Lars is AI,’ wrote another.”

FUTURE OF FOOD
KFC Is Working With a Russian 3D Bioprinting Firm to Try to Make Lab-Produced Chicken Nuggets
Kim Lyons | The Verge
“The chicken restaurant chain will work with Russian company 3D Bioprinting Solutions to develop bioprinting technology that will ‘print’ chicken meat, using chicken cells and plant material. KFC plans to provide the bioprinting firm with ingredients like breading and spices ‘to achieve the signature KFC taste’ and will seek to replicate the taste and texture of genuine chicken.”

BIOTECH
A CRISPR Cow Is Born. It’s Definitely a Boy
Megan Molteni | Wired
“After nearly five years of research, at least half a million dollars, dozens of failed pregnancies, and countless scientific setbacks, Van Eenennaam’s pioneering attempt to create a line of Crispr’d cattle tailored to the needs of the beef industry all came down to this one calf. Who, as luck seemed sure to have it, was about to enter the world in the middle of a global pandemic.”

GOVERNANCE
Is the Pandemic Finally the Moment for a Universal Basic Income?
Brooks Rainwater and Clay Dillow | Fast Company
“Since February, governments around the globe—including in the US—have intervened in their citizens’ individual financial lives, distributing direct cash payments to backstop workers sidelined by the COVID-19 pandemic. Some are considering keeping such direct assistance in place indefinitely, or at least until the economic shocks subside.”

SCIENCE
How Gödel’s Proof Works
Natalie Wolchover | Wired
“In 1931, the Austrian logician Kurt Gödel pulled off arguably one of the most stunning intellectual achievements in history. Mathematicians of the era sought a solid foundation for mathematics: a set of basic mathematical facts, or axioms, that was both consistent—never leading to contradictions—and complete, serving as the building blocks of all mathematical truths. But Gödel’s shocking incompleteness theorems, published when he was just 25, crushed that dream.”

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Posted in Human Robots

#437261 How AI Will Make Drug Discovery ...

If you had to guess how long it takes for a drug to go from an idea to your pharmacy, what would you guess? Three years? Five years? How about the cost? $30 million? $100 million?

Well, here’s the sobering truth: 90 percent of all drug possibilities fail. The few that do succeed take an average of 10 years to reach the market and cost anywhere from $2.5 billion to $12 billion to get there.

But what if we could generate novel molecules to target any disease, overnight, ready for clinical trials? Imagine leveraging machine learning to accomplish with 50 people what the pharmaceutical industry can barely do with an army of 5,000.

Welcome to the future of AI and low-cost, ultra-fast, and personalized drug discovery. Let’s dive in.

GANs & Drugs
Around 2012, computer scientist-turned-biophysicist Alex Zhavoronkov started to notice that artificial intelligence was getting increasingly good at image, voice, and text recognition. He knew that all three tasks shared a critical commonality. In each, massive datasets were available, making it easy to train up an AI.

But similar datasets were present in pharmacology. So, back in 2014, Zhavoronkov started wondering if he could use these datasets and AI to significantly speed up the drug discovery process. He’d heard about a new technique in artificial intelligence known as generative adversarial networks (or GANs). By pitting two neural nets against one another (adversarial), the system can start with minimal instructions and produce novel outcomes (generative). At the time, researchers had been using GANs to do things like design new objects or create one-of-a-kind, fake human faces, but Zhavoronkov wanted to apply them to pharmacology.

He figured GANs would allow researchers to verbally describe drug attributes: “The compound should inhibit protein X at concentration Y with minimal side effects in humans,” and then the AI could construct the molecule from scratch. To turn his idea into reality, Zhavoronkov set up Insilico Medicine on the campus of Johns Hopkins University in Baltimore, Maryland, and rolled up his sleeves.

Instead of beginning their process in some exotic locale, Insilico’s “drug discovery engine” sifts millions of data samples to determine the signature biological characteristics of specific diseases. The engine then identifies the most promising treatment targets and—using GANs—generates molecules (that is, baby drugs) perfectly suited for them. “The result is an explosion in potential drug targets and a much more efficient testing process,” says Zhavoronkov. “AI allows us to do with fifty people what a typical drug company does with five thousand.”

The results have turned what was once a decade-long war into a month-long skirmish.

In late 2018, for example, Insilico was generating novel molecules in fewer than 46 days, and this included not just the initial discovery, but also the synthesis of the drug and its experimental validation in computer simulations.

Right now, they’re using the system to hunt down new drugs for cancer, aging, fibrosis, Parkinson’s, Alzheimer’s, ALS, diabetes, and many others. The first drug to result from this work, a treatment for hair loss, is slated to start Phase I trials by the end of 2020.

They’re also in the early stages of using AI to predict the outcomes of clinical trials in advance of the trial. If successful, this technique will enable researchers to strip a bundle of time and money out of the traditional testing process.

Protein Folding
Beyond inventing new drugs, AI is also being used by other scientists to identify new drug targets—that is, the place to which a drug binds in the body and another key part of the drug discovery process.

Between 1980 and 2006, despite an annual investment of $30 billion, researchers only managed to find about five new drug targets a year. The trouble is complexity. Most potential drug targets are proteins, and a protein’s structure—meaning the way a 2D sequence of amino acids folds into a 3D protein—determines its function.

But a protein with merely a hundred amino acids (a rather small protein) can produce a googol-cubed worth of potential shapes—that’s a one followed by three hundred zeroes. This is also why protein-folding has long been considered an intractably hard problem for even the most powerful of supercomputers.

Back in 1994, to monitor supercomputers’ progress in protein-folding, a biannual competition was created. Until 2018, success was fairly rare. But then the creators of DeepMind turned their neural networks loose on the problem. They created an AI that mines enormous datasets to determine the most likely distance between a protein’s base pairs and the angles of their chemical bonds—aka, the basics of protein-folding. They called it AlphaFold.

On its first foray into the competition, contestant AIs were given 43 protein-folding problems to solve. AlphaFold got 25 right. The second-place team managed a meager three. By predicting the elusive ways in which various proteins fold on the basis of their amino acid sequences, AlphaFold may soon have a tremendous impact in aiding drug discovery and fighting some of today’s most intractable diseases.

Drug Delivery
Another theater of war for improved drugs is the realm of drug delivery. Even here, converging exponential technologies are paving the way for massive implications in both human health and industry shifts.

One key contender is CRISPR, the fast-advancing gene-editing technology that stands to revolutionize synthetic biology and treatment of genetically linked diseases. And researchers have now demonstrated how this tool can be applied to create materials that shape-shift on command. Think: materials that dissolve instantaneously when faced with a programmed stimulus, releasing a specified drug at a highly targeted location.

Yet another potential boon for targeted drug delivery is nanotechnology, whereby medical nanorobots have now been used to fight incidences of cancer. In a recent review of medical micro- and nanorobotics, lead authors (from the University of Texas at Austin and University of California, San Diego) found numerous successful tests of in vivo operation of medical micro- and nanorobots.

Drugs From the Future
Covid-19 is uniting the global scientific community with its urgency, prompting scientists to cast aside nation-specific territorialism, research secrecy, and academic publishing politics in favor of expedited therapeutic and vaccine development efforts. And in the wake of rapid acceleration across healthcare technologies, Big Pharma is an area worth watching right now, no matter your industry. Converging technologies will soon enable extraordinary strides in longevity and disease prevention, with companies like Insilico leading the charge.

Riding the convergence of massive datasets, skyrocketing computational power, quantum computing, cognitive surplus capabilities, and remarkable innovations in AI, we are not far from a world in which personalized drugs, delivered directly to specified targets, will graduate from science fiction to the standard of care.

Rejuvenational biotechnology will be commercially available sooner than you think. When I asked Alex for his own projection, he set the timeline at “maybe 20 years—that’s a reasonable horizon for tangible rejuvenational biotechnology.”

How might you use an extra 20 or more healthy years in your life? What impact would you be able to make?

Join Me
(1) A360 Executive Mastermind: If you’re an exponentially and abundance-minded entrepreneur who would like coaching directly from me, consider joining my Abundance 360 Mastermind, a highly selective community of 360 CEOs and entrepreneurs who I coach for 3 days every January in Beverly Hills, Ca. Through A360, I provide my members with context and clarity about how converging exponential technologies will transform every industry. I’m committed to running A360 for the course of an ongoing 25-year journey as a “countdown to the Singularity.”

If you’d like to learn more and consider joining our 2021 membership, apply here.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs—those who want to get involved and play at a higher level. Click here to learn more.

(Both A360 and Abundance-Digital are part of Singularity University—your participation opens you to a global community.)

This article originally appeared on diamandis.com. Read the original article here.

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Posted in Human Robots

#437258 This Startup Is 3D Printing Custom ...

Around 1.9 million people in the US are currently living with limb loss. The trauma of losing a limb is just the beginning of what amputees have to face, with the sky-high cost of prosthetics making their circumstance that much more challenging.

Prosthetics can run over $50,000 for a complex limb (like an arm or a leg) and aren’t always covered by insurance. As if shelling out that sum one time wasn’t costly enough, kids’ prosthetics need to be replaced as they outgrow them, meaning the total expense can reach hundreds of thousands of dollars.

A startup called Unlimited Tomorrow is trying to change this, and using cutting-edge technology to do so. Based in Rhinebeck, New York, a town about two hours north of New York City, the company was founded by 23-year-old Easton LaChappelle. He’d been teaching himself the basics of robotics and building prosthetics since grade school (his 8th grade science fair project was a robotic arm) and launched his company in 2014.

After six years of research and development, the company launched its TrueLimb product last month, describing it as an affordable, next-generation prosthetic arm using a custom remote-fitting process where the user never has to leave home.

The technologies used for TrueLimb’s customization and manufacturing are pretty impressive, in that they both cut costs and make the user’s experience a lot less stressful.

For starters, the entire purchase, sizing, and customization process for the prosthetic can be done remotely. Here’s how it works. First, prospective users fill out an eligibility form and give information about their residual limb. If they’re a qualified candidate for a prosthetic, Unlimited Tomorrow sends them a 3D scanner, which they use to scan their residual limb.

The company uses the scans to design a set of test sockets (the component that connects the residual limb to the prosthetic), which are mailed to the user. The company schedules a video meeting with the user for them to try on and discuss the different sockets, with the goal of finding the one that’s most comfortable; new sockets can be made based on the information collected during the video consultation. The user selects their skin tone from a swatch with 450 options, then Unlimited Tomorrow 3D prints and assembles the custom prosthetic and tests it before shipping it out.

“We print the socket, forearm, palm, and all the fingers out of durable nylon material in full color,” LaChappelle told Singularity Hub in an email. “The only components that aren’t 3D printed are the actuators, tendons, electronics, batteries, sensors, and the nuts and bolts. We are an extreme example of final use 3D printing.”

Unlimited Tomorrow’s website lists TrueLimb’s cost as “as low as $7,995.” When you consider the customization and capabilities of the prosthetic, this is incredibly low. According to LaChappelle, the company created a muscle sensor that picks up muscle movement at a higher resolution than the industry standard electromyography sensors. The sensors read signals from nerves in the residual limb used to control motions like fingers bending. This means that when a user thinks about bending a finger, the nerve fires and the prosthetic’s sensors can detect the signal and translate it into the action.

“Working with children using our device, I’ve witnessed a physical moment where the brain “clicks” and starts moving the hand rather than focusing on moving the muscles,” LaChappelle said.

The cost savings come both from the direct-to-consumer model and the fact that Unlimited Tomorrow doesn’t use any outside suppliers. “We create every piece of our product,” LaChappelle said. “We don’t rely on another prosthetic manufacturer to make expensive sensors or electronics. By going direct to consumer, we cut out all the middlemen that usually drive costs up.” Similar devices on the market can cost up to $100,000.

Unlimited Tomorrow is primarily focused on making prosthetics for kids; when they outgrow their first TrueLimb, they send it back, where the company upcycles the expensive quality components and integrates them into a new customized device.

Unlimited Tomorrow isn’t the first to use 3D printing for prosthetics. Florida-based Limbitless Solutions does so too, and industry experts believe the technology is the future of artificial limbs.

“I am constantly blown away by this tech,” LaChappelle said. “We look at technology as the means to augment the human body and empower people.”

Image Credit: Unlimited Tomorrow Continue reading

Posted in Human Robots

#437209 A Renaissance of Genomics and Drugs Is ...

The causes of aging are extremely complex and unclear. But with longevity clinical trials increasing, more answers—and questions—are emerging than ever before.

With the dramatic demonetization of genome reading and editing over the past decade, and Big Pharma, startups, and the FDA starting to face aging as a disease, we are starting to turn those answers into practical ways to extend our healthspan.

In this article, I’ll explore how genome sequencing and editing, along with new classes of anti-aging drugs, are augmenting our biology to further extend our healthy lives.

Genome Sequencing and Editing
Your genome is the software that runs your body. A sequence of 3.2 billion letters makes you “you.” These base pairs of A’s, T’s, C’s, and G’s determine your hair color, your height, your personality, your propensity for disease, your lifespan, and so on.

Until recently, it’s been very difficult to rapidly and cheaply “read” these letters—and even more difficult to understand what they mean. Since 2001, the cost to sequence a whole human genome has plummeted exponentially, outpacing Moore’s Law threefold. From an initial cost of $3.7 billion, it dropped to $10 million in 2006, and to $1,500 in 2015.

Today, the cost of genome sequencing has dropped below $600, and according to Illumina, the world’s leading sequencing company, the process will soon cost about $100 and take about an hour to complete.

This represents one of the most powerful and transformative technology revolutions in healthcare. When we understand your genome, we’ll be able to understand how to optimize “you.”

We’ll know the perfect foods, the perfect drugs, the perfect exercise regimen, and the perfect supplements, just for you.
We’ll understand what microbiome types, or gut flora, are ideal for you (more on this in a later article).
We’ll accurately predict how specific sedatives and medicines will impact you.
We’ll learn which diseases and illnesses you’re most likely to develop and, more importantly, how to best prevent them from developing in the first place (rather than trying to cure them after the fact).

CRISPR Gene Editing
In addition to reading the human genome, scientists can now edit a genome using a naturally occurring biological system discovered in 1987 called CRISPR/Cas9.

Short for Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9, the editing system was adapted from a naturally-occurring defense system found in bacteria.

Here’s how it works. The bacteria capture snippets of DNA from invading viruses (or bacteriophage) and use them to create DNA segments known as CRISPR arrays. The CRISPR arrays allow the bacteria to “remember” the viruses (or closely related ones), and defend against future invasions. If the viruses attack again, the bacteria produce RNA segments from the CRISPR arrays to target the viruses’ DNA. The bacteria then use Cas9 to cut the DNA apart, which disables the virus.

Most importantly, CRISPR is cheap, quick, easy to use, and more accurate than all previous gene editing methods. As a result, CRISPR/Cas9 has swept through labs around the world as the way to edit a genome. A short search in the literature will show an exponential rise in the number of CRISPR-related publications and patents.

2018: Filled With CRISPR Breakthroughs
Early results are impressive. Researchers have used CRISPR to genetically engineer cocaine resistance into mice, reverse the gene defect causing Duchenne muscular dystrophy (DMD) in dogs, and reduce genetic deafness in mice.

Already this year, CRISPR-edited immune cells have been shown to successfully kill cancer cells in human patients. Researchers have discovered ways to activate CRISPR with light and use the gene-editing technology to better understand Alzheimer’s disease progression.

With great power comes great responsibility, and the opportunity for moral and ethical dilemmas. In 2015, Chinese scientists sparked global controversy when they first edited human embryo cells in the lab with the goal of modifying genes that would make the child resistant to smallpox, HIV, and cholera. Three years later, in November 2018, researcher He Jiankui informed the world that the first set of CRISPR-engineered female twins had been delivered.

To accomplish his goal, Jiankui deleted a region of a receptor on the surface of white blood cells known as CCR5, introducing a rare, natural genetic variation that makes it more difficult for HIV to infect its favorite target, white blood cells. Because Jiankui forged ethical review documents and misled doctors in the process, he was sentenced to three years in prison and fined $429,000 last December.

Coupled with significant ethical conversations necessary for progress, CRISPR will soon provide us the tools to eliminate diseases, create hardier offspring, produce new environmentally resistant crops, and even wipe out pathogens.

Senolytics, Nutraceuticals, and Pharmaceuticals
Over the arc of your life, the cells in your body divide until they reach what is known as the Hayflick limit, or the number of times a normal human cell population will divide before cell division stops, which is typically about 50 divisions.

What normally follows next is programmed cell death or destruction by the immune system. A very small fraction of cells, however, become senescent cells and evade this fate to linger indefinitely. These lingering cells secrete a potent mix of molecules that triggers chronic inflammation, damages the surrounding tissue structures, and changes the behavior of nearby cells for the worse. Senescent cells appear to be one of the root causes of aging, causing everything from fibrosis and blood vessel calcification to localized inflammatory conditions such as osteoarthritis to diminished lung function.

Fortunately, both the scientific and entrepreneurial communities have begun to work on senolytic therapies, moving the technology for selectively destroying senescent cells out of the laboratory and into a half-dozen startup companies.

Prominent companies in the field include the following:

Unity Biotechnology is developing senolytic medicines to selectively eliminate senescent cells with an initial focus on delivering localized therapy in osteoarthritis, ophthalmology, and pulmonary disease.

Oisin Biotechnologies is pioneering a programmable gene therapy that can destroy cells based on their internal biochemistry.

SIWA Therapeutics is working on an immunotherapy approach to the problem of senescent cells.

In recent years, researchers have identified or designed a handful of senolytic compounds that can curb aging by regulating senescent cells. Two of these drugs that have gained mainstay research traction are rapamycin and metformin.

(1) Rapamycin

Originally extracted from bacteria found on Easter Island, rapamycin acts on the m-TOR (mechanistic target of rapamycin) pathway to selectively block a key protein that facilitates cell division. Currently, rapamycin derivatives are widely used for immunosuppression in organ and bone marrow transplants. Research now suggests that use results in prolonged lifespan and enhanced cognitive and immune function.

PureTech Health subsidiary resTORbio (which went public in 2018) is working on a rapamycin-based drug intended to enhance immunity and reduce infection. Their clinical-stage RTB101 drug works by inhibiting part of the mTOR pathway.

Results of the drug’s recent clinical trial include decreased incidence of infection, improved influenza vaccination response, and a 30.6 percent decrease in respiratory tract infection.

Impressive, to say the least.

(2) Metformin

Metformin is a widely-used generic drug for mitigating liver sugar production in Type 2 diabetes patients. Researchers have found that metformin also reduces oxidative stress and inflammation, which otherwise increase as we age. There is strong evidence that metformin can augment cellular regeneration and dramatically mitigate cellular senescence by reducing both oxidative stress and inflammation.

Over 100 studies registered on ClinicalTrials.gov are currently following up on strong evidence of metformin’s protective effect against cancer.

(3) Nutraceuticals and NAD+

Beyond cellular senescence, certain critical nutrients and proteins tend to decline as a function of age. Nutraceuticals combat aging by supplementing and replenishing these declining nutrient levels.

NAD+ exists in every cell, participating in every process from DNA repair to creating the energy vital for cellular processes. It’s been shown that NAD+ levels decline as we age.

The Elysium Health Basis supplement aims to elevate NAD+ levels in the body to extend one’s lifespan. Elysium’s first clinical study reports that Basis increases NAD+ levels consistently by a sustained 40 percent.

Conclusion
These are just a taste of the tremendous momentum that longevity and aging technology has right now. As artificial intelligence and quantum computing transform how we decode our DNA and how we discover drugs, genetics and pharmaceuticals will become truly personalized.

The next article in this series will demonstrate how artificial intelligence is converging with genetics and pharmaceuticals to transform how we approach longevity, aging, and vitality.

We are edging closer toward a dramatically extended healthspan—where 100 is the new 60. What will you create, where will you explore, and how will you spend your time if you are able to add an additional 40 healthy years to your life?

Join Me
(1) A360 Executive Mastermind: If you’re an exponentially and abundance-minded entrepreneur who would like coaching directly from me, consider joining my Abundance 360 Mastermind, a highly selective community of 360 CEOs and entrepreneurs who I coach for 3 days every January in Beverly Hills, Ca. Through A360, I provide my members with context and clarity about how converging exponential technologies will transform every industry. I’m committed to running A360 for the course of an ongoing 25-year journey as a “countdown to the Singularity.”

If you’d like to learn more and consider joining our 2021 membership, apply here.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs—those who want to get involved and play at a higher level. Click here to learn more.

(Both A360 and Abundance-Digital are part of Singularity University—your participation opens you to a global community.)

This article originally appeared on diamandis.com. Read the original article here.

Image Credit: Arek Socha from Pixabay Continue reading

Posted in Human Robots