- We’ve hit a huge milestone with nuclear fusion…
- The top AI research team releases another innovation…
- “I don’t care how you do it; just get the job done”…
Yesterday turned out to be quite a disappointment… It was supposed to be a historic day, yet nothing happened.
NASA’s Artemis I mission was scheduled to launch, marking NASA’s return to the moon for the first time since 1972. It’s hard to believe that it has been 50 years since the last visit.
Ironically, the mission is less ambitious than what was done back in the days of the Apollo program. Artemis I is an uncrewed flight that will insert itself into orbit around the moon for somewhere between six and 19 days, and then return to Earth for an ultimate splashdown in the Pacific Ocean. It’s basically just a test run.
It wasn’t weather, though, that caused the delay. NASA’s Space Launch System (SLS) ran into some troubles… again. One of its liquid hydrogen lines started leaking, then one of its four massive engines wasn’t cooling properly. Then a crack appeared in the foam insulation around the tanks that was first thought to be between the tanks themselves.
Sadly, this has been par for the course for NASA’s SLS. Years of delays and problems, billions of dollars over budget… And we’re still waiting. The next two launch windows bookend the upcoming Labor Day holiday weekend, on September 2 and September 5.
I have very mixed feelings about the SLS. It’s exciting to see such an ambitious program that, if successful, would return us to the moon and eventually beyond. But from an objective point of view, this program should be scrapped.
That might come as a surprise to hear me say that. After all, my background is in aeronautical and astronautical engineering.
But each Artemis mission costs taxpayers $4.1 billion. And the total cost of the program between 2012 and 2025 is currently estimated at $93 billion.
It’s one thing if NASA didn’t have any alternative. But it does… And the numbers are shocking.
SpaceX currently launches payloads on its smaller Falcon 9 rocket for $67 million. And SpaceX CEO Elon Musk has stated that within a few years, the cost to launch its Starship with the Super Heavy booster, which is more capable than the SLS, will be less than $10 million.
Compared to the SLS, that cost would equate to just 0.24% of the cost of a single SLS launch. Even if we assumed that the SpaceX costs were $100 million a launch, the price would still be just 2.4% of NASA’s SLS. And the SpaceX rocket and spacecraft are capable of lifting more payload than the SLS.
Aside from superior engineering, the SpaceX technology is reusable. And as we’ve already seen, the Starship is capable of landing vertically on a launch pad, thus eliminating any recovery costs. It is superior on all counts and can be used at a fraction of the price.
NASA’s SLS program has been an embarrassment for NASA and the aerospace companies involved. Regardless of whether or not the Artemis I mission is successful, it’s time to put the program to rest. The advantages of going all in with SpaceX are simply too great… both in terms of performance, as well as in savings for taxpayers.
Here’s to going to the moon on a Starship…
Unlimited clean energy through nuclear fusion is no longer a theory…
Last September, we talked about an interesting development from the National Ignition Facility (NIF), a research lab at the Lawrence Livermore National Laboratory in California.
If we remember, the NIF research team performed a nuclear fusion experiment using a very different approach. They focused 192 high-powered laser beams on a tiny capsule of hydrogen, about the size of a BB-gun pellet.
The lasers hit the capsule for less than a second, and the hydrogen heated up to 18,000 times hotter than the Sun. This created intense pressure… And that caused the hydrogen atoms to fuse, releasing 1.3 megajoules of energy – the equivalent of 10 quadrillion watts of power.
As we would expect, this was the highest energy yield the facility had ever seen.
So we were very excited about this breakthrough at the time. But it turns out we didn’t realize just how incredible it was…
The research team has been analyzing the data from the experiment for nearly a year now. And they determined that the reaction wasn’t just temporary. It reached “Lawson’s criterion.”
Lawson’s criterion is the point at which a fusion reaction becomes self-sustaining. It’s where one fusion reaction leads to another… and another… and so on. It continues as long as the reactor is kept on, assuming the same conditions can be maintained.
This is the holy grail of nuclear fusion. It’s where the energy produced exceeds the energy needed to start and maintain the reaction. When this happens, it results in limitless, clean energy that will ultimately result in the lowest cost of energy production that we’ve ever seen.
So nuclear fusion technology is no longer a theory.
And the NIF team’s next step is simply to recreate the reaction for longer durations. They are furiously working to identify the exact conditions that enabled the first reaction to achieve Lawson’s criterion. From there, the team will work on methods to reproduce the reaction at will.
The was a remarkable breakthrough, and it’s even more interesting that the team needed a year to figure out just how significant the event had been.
I’m sure regular readers of The Bleeding Edge have noticed that the frequency of developments related to nuclear fusion has been increasing. This is always the case in emerging technologies that are coming to age and ultimately into commercialization.
This year has already been a remarkable year, and I believe that by 2024 – at the latest – we’ll see the first sustained nuclear fusion reactor producing net energy output. And in the years that follow, energy shortages will quickly become a distant memory… as will coal and natural gas plants.
DeepMind is at it again…
Just two weeks ago, we talked about how DeepMind solved one of biotechnology’s grand challenges… One that will change drug discovery and development forever.
Well, the team at DeepMind just released yet another artificial intelligence (AI) breakthrough. This one is based on a neural network applied to images and video.
Specifically, DeepMind just demonstrated an AI framework that can create 30-second videos from just a single image.
Here’s an example:
Image to Video
I’ll explain what we are seeing here with a little context…
When we see the frame “jump” back to the beginning of the loop, that’s the original image. The video that follows has been generated by the AI. It’s artificially generated content.
From a single image, the AI can predict what would likely follow in the environment shown in the image. And it looks completely real.
This is impressive technology. And there are some very interesting applications.
If we think about virtual reality (VR), video games, and metaverses, this technology could quickly create content for all of them. Using a series of still images, developers could create incredibly immersive content in a very short period of time.
So I think this is something that various industries will adopt very quickly. DeepMind continues to consistently demonstrate remarkable agility in applying AI to many different industries and applications.
“Pretrained” AI will save lives…
We’ll wrap up today with another interesting development on the AI front. This one comes from a team of researchers at Santa Clara University and the University of Hong Kong – They developed a process for teaching micro-robots how to swim.
Here’s why this is such a breakthrough…
We talked about how micro-robotics could enable remote surgeries back in July. The concept is that the world’s top surgeons could use remote-controlled micro-robots to perform surgery on patients anywhere in the world.
That’s a fantastic development. But it still requires the surgeon to manually control the robots.
By teaching micro-robots to swim, the team from Santa Clara and the University of Hong Kong introduced the possibility of autonomous surgeries.
For example, we could use these micro-robots to clean out congested arteries. Simply insert them into a patient, program them with the end goal, and they’ll figure out how to get to the right spot and get to work.
And what about tumor cells? It’s feasible we could program micro-robots to break down malignant cells in the body as a way to treat cancer.
Again, if the bots can already swim autonomously inside the body, all they need to know is the end goal. It’s like a manager saying to somebody, “I don’t care how you do it; just get the job done.”
It’s like having an army of “pre-trained” micro-robots that can be deployed to solve complex problems. They already know how to maneuver themselves within the body. We can simply program them to perform specific medical tasks, and they’ll do the rest.
This approach miniaturizes robotic surgery, avoids the need for large incisions, and automates the task. And as this technology develops – and eventually attains FDA approval – it will reduce costs and increase efficacy for many surgical procedures.
Editor, The Bleeding Edge