How Self-Driving Cars Handle Bad Weather

• How will self-driving cars handle bad weather?

• Is blockchain technology at risk?

• extinction of chemotherapy?

Dear Reader,

Happy New Year, and welcome to the first weekly mailbag edition of The Bleeding Edge this year. I sincerely hope that you all had a fantastic and restful break over the holidays with family and friends.

Over the last couple of weeks, you submitted your questions about the biggest trends in technology. Thanks for the questions over the holidays. I’ll do my best to answer them.

If you have a question you’d like answered next week, be sure you submit it right here.

I’d like to wish you all the best for a healthy and prosperous 2022.

Driving in rain or shine…

Let’s begin with self-driving cars in bad conditions:

Dear Jeff: Living where [you do] is what allows you to talk the way you do about these marvelous self-driving electric vehicles. But how will they react to a sudden snowstorm on icy highways with zero visibility? Or worse: sheet ice on a steep mountain road going skiing?

How will they react to overnight temperatures dropping way below zero and “flat-sided” tires? How will they negotiate a sandstorm? Townies in mild climates may be listening… but we northern folk are still skeptical. Can you address this? When will they match our requirements?

– Geoff D.

Hi, Geoff. This a great topic, and thanks for sharing your skepticism. I can relate.

One of my best memories as a kid growing up in the suburbs of Chicago was the blizzard ’79. Unbelievable. I remember having 6-foot snow drifts. I was able to jump off the second floor of my house into a drift. As a kid, it was fantastic. For everyone else, it was a complete mess.

Inclement weather of many sorts does pose additional challenges for autonomous vehicles. Snow, ice, heavy rain, and dense fog can be a challenge at present.

Snow, for instance, can obscure our vision, increase glare, and reduce tire traction. Snow driving also requires different techniques. We must limit our speed more than usual, avoid lots of stopping and starting, and must be extra cautious when going up and down snowy or icy hills – as just a few examples.

That’s why some companies are initially focusing on areas that tend to have milder climates.

Ryder, for instance, is building out its self-driving trucking network across the southern half of the U.S., where there’s less likelihood of snow and ice.

But rest assured… Many companies are working on complex driving situations. As I wrote late last year, Amazon is testing its self-driving vehicles in Seattle on purpose.

It chose Seattle specifically because it offers a difficult driving environment. There are a lot of one-way streets, narrow tunnels, and, of course, inclement weather. It’s often rainy or foggy in Seattle.

And Tesla, of course, is also working hard on this issue. It’s adopting neural networks to make the latest versions of its self-driving software adaptable to any driving conditions. It can learn, in real time, in a similar way that the human brain learns.

And it has the benefit of learning from not just one driving experience, but hundreds of thousands, if not millions, of driving experiences. Unlike human beings, its training is derived from the combined learnings of billions of miles driven, not just from the singular experience of one driver.

That’s why having a large database to pull from is so important in this field. Tesla currently leads the pack in this area, with over five billion miles recorded on Autopilot as of last year. This is one of Tesla’s big advantages over the competition.

Right now, Teslas still require driver awareness and readiness to intervene. But as more and more drivers practice maneuvering in all kinds of complex conditions, we’ll continue to see rapid improvements in its self-driving technology.

The artificial intelligence (AI) behind Tesla’s system continues to learn how to respond in snow, fog, or other challenging situations as its Autopilot program becomes more experienced.

And we should keep in mind that as human drivers, we are “limited” to our vision and our “feel” of the road through the steering wheel. The sensors on an autonomous car not only include vision and “feel,” but infrared, radar, and, for some cars, LIDAR (light detection and ranging) as well.

Versatile, fully autonomous technology is here today, and it has already been demonstrated in some capacity by Tesla. My prediction is that Tesla will roll out this technology to its fleet of cars this year, setting the stage for what will ultimately become a shared autonomous vehicle network.

And when this happens, we should always remember… In the rare situations where an autonomous vehicle simply doesn’t know what to do, it can stop, pull over, or ask us to take over control of the car.

From there, it will “watch” to see how we navigate the situation. And it will “learn” and “remember” and share that learning with every other vehicle of its kind on the planet. The feedback loop will be fast and permanent.

That’s also why this has been a big investment theme for my readers. If you’d like to know about some of my top recommendations in this space, simply go right here for more details.

Can quantum computers threaten blockchains?

Next, a reader wants to know more about blockchain cybersecurity:

If/when quantum computers crack 256-bit encryption, will the blockchain be the answer to cybersecurity? Will we need to worry about cybersecurity on the blockchain? Thanks for all your work.

– Glenn J.

Hi, Glenn, and thank you for being a reader. Your question is not only important, but it is far timelier than we might think.

One of my predictions for this year is that a major player in quantum computing will announce a 256 quantum bit (qubit) computer within the next 12 months. If I’m right, this will become a very hot topic overnight.

This topic has worried people ever since Google achieved quantum supremacy back in September 2019. That was the point at which a quantum computer could outperform the most powerful classical supercomputer on Earth.

Quantum computing will be a threat to blockchain technology. After all, blockchains are cryptographically secured. Yet a quantum computer can theoretically hack the cryptography of many blockchains…

That said, current quantum computers are too “noisy” right now to do it. Said another way, they are not fault-tolerant enough to perform such a feat… but they are getting close.

IBM unveiled its 127-qubit quantum processor in November of last year. It plans to release a 433-qubit quantum computer sometime this year.

And it intends to reach 1,000 qubits by 2023. This is questionable, and numbers like these only matter if the “noise” can be controlled. It is somewhat of a vanity metric that depends heavily on the ability of the system to control errors.

But if the system can adjust for noise, this kind of computing power could crack 256-bit encryption in seconds. And my prediction is that a fault-tolerant, 256-qubit quantum computer will be announced this year.

And this is why the cybersecurity industry is scrambling. The National Institute for Standards and Technology (NIST), a division of the U.S. Department of Commerce, is already working on quantum-resistant encryption technology, and it’s not alone.

There is some nuance in this subject worth mentioning as well. For example, proof-of-work blockchain technology is very much at risk of being cracked by quantum computers. Proof-of-stake blockchain technology is actually more resistant to quantum computers, though.

And while quantum computers will threaten the integrity of blockchain technology, there is one very important thing to remember.

Blockchain technology is software. And like all software, it can be upgraded. That’s one reason why I’m still very bullish about the future of the blockchain industry.

Private companies are currently working on solutions to make blockchains “quantum-proof.” One blockchain project called Quantum Resistant Ledger has even developed its blockchain technology from the ground up to be quantum-resistant.

And we’re going to see a lot more work in this area as we get closer to universal fault-tolerant quantum computers.

Ultimately, the industry hasn’t been sitting on the sidelines. There’s plenty of motivation to solve this problem.

After all, if quantum computers pose a threat to popular blockchains, they also threaten the encryption that protects our governments, militaries, corporations, and e-commerce websites.

So any company that manages to solve these problems will be in high demand.

That’s why we’ll be keeping a close eye on the developments in cryptography and cybersecurity in 2022.

Promising companies in this area will make a very smart investment as we adjust to a world full of quantum computers and computing systems run entirely by artificial intelligence.

Improving cancer treatments…

Let’s conclude with a question about the convergence of AI and biotech:

Hello, Jeff – with all the advancements being made and worked on in new therapies via artificial intelligence (AI)/machine learning (ML) [applied to] drug discovery and personalized medicine, do you have a prediction for the extinction of chemotherapy for cancer patients?

– Gary S.

Hi, Gary, and thanks for writing in. This is a key topic we’re covering here in The Bleeding Edge. AI and ML have done incredible things for the biotech industry and drug development process.

As we know, traditional cancer treatments like chemotherapy, radiation, and even surgery basically burn everything down, hoping to take out the cancerous cells in the process. It’s a miserable experience for patients… And the chances of success are low for patients who have advanced stages of cancer.

Yet cutting-edge companies are working to create far more effective – and less painful – alternatives to these kinds of treatments.

For example, last year, I wrote about Deep Genomics’ work. The company is developing an AI-enhanced approach to genetic editing. When a genetic mutation causes cells to produce the wrong proteins, Deep Genomics can then simply “turn off” those cells.

Of course, specificity is key with gene editing since we don’t want any off-target changes. The good news is, Deep Genomics can target specific areas of our DNA for treatment.

What makes genetic editing technology like this so exciting is that it is the definition of precision medicine. It’s designed to be precise and go straight to its desired target… instead of a therapy that affects the entire body like chemotherapy. One day soon, we may be able to target cancer cells specifically.

AI/ML are also being used to understand how proteins fold, how proteins interact with different compounds, and how individual DNA interacts with specific therapeutic approaches.

In time, physicians will be able to feed our DNA into a system, run an analysis, and quickly determine what the best course of treatment will be based on our own makeup.

As I often say, I believe we’re on the path to curing many human diseases previously thought to be incurable. There is so much progress being made in the biotechnology space. And AI/ML is speeding that progress up… and creating new ways of thinking about medicine.

That’s something we have to look forward to, and it’s a trend we’ll continue to watch throughout 2022. It’s also one of the biggest investment opportunities I’ll keep on investors’ radar. And to learn about my favorite convergence company right now, please go right here.

And I’ll close this out with a final comment. This is a topic that is deeply personal to me right now as I am experiencing my own health challenge – prostate cancer.

The “easy” button is to just cut it out. But because I was proactive in identifying it early, I’ve got a shot at beating it. My goal is to reverse it.

Through my efforts, study, and support from a great medical team, I have begun to deeply understand the effect of our diet and lifestyle choices on our health.

Yes, part of the problem depends on our genetic makeup, but most of our health problems are caused by our consumption and the quality and regularity of our exercise.

This process of learning, and being honest with myself, has been enlightening… and humbling. It has also been empowering, because I recognize that there are changes that I can make to impact a far better outcome for my health and my own longevity.

And who knows, if I work hard enough, I may be able to reverse the cancer and avoid surgery all together. All I know is that I’m up for the fight.

At the moment, some of these advanced precision medicine techniques are not available to me. But it won’t be long before they are.

So, if I can offer a piece of advice, now is the time to make extra efforts to take care of our health. If we can stay in good health for the next five to seven years, I believe that the range of therapeutic options will be remarkably better than what is available to us today.

That’s all we have time for this week. If you have a question for a future mailbag, you can send it to me right here.

Let’s have a great year, and I wish you all a healthy and Happy New Year.

Regards,

Jeff Brown
Editor, The Bleeding Edge

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