But for the most part, Blue Origin is falling behind its peers. SpaceX’s Falcon 9 rocket (reusable, and capable of going all the way into orbit) has flown more than 100 missions, with a remarkable track record of success since 2016. Its Falcon Heavy is the most powerful rocket today. Even smaller companies can boast more business than Blue Origin. Rocket Lab, for instance, has nearly perfected the design of its lightweight Electron rocket, which features 3D-printed engines that are cheaper and faster to make. In 18 missions, Electron has delivered more satellites into space than Blue Origin. And it’s already got plans to send a probe to Venus in a few years.
Blue Origin could catch up, though. Several new projects under way could position the company to finally start competing directly with SpaceX and others, and generate steady revenue from a regular line of customers (no more selling off Amazon stock to fund it). Having Bezos more involved in the day-to-day could be a big asset in securing those customers and inking contracts that really put the company on the map.
Here are the six ongoing Blue Origin projects that Bezos could bolster now that he has more time on his hands.
Human spaceflight
New Shepard was developed with one major goal in mind: to safely and affordably send people into space on suborbital missions, where they could spend a few minutes in microgravity and enjoy the view of the planet from high up. In its current design, it should be able to take six passengers at once on these missions.
The company was hoping for a crewed New Shepard flight in 2019. That didn’t happen. And the pandemic put a stop to most of the company’s launch activities in 2020. Everyone’s waiting patiently to see if 2021 is the golden year, but that looks pretty unlikely at the moment.
Bezos himself can’t do anything to speed up testing and development of New Shepard and get it ready for human spaceflight. But the same way Musk is an evangelist for generating interest in SpaceX, Bezos could play the same role by being the salesman he is, getting people interested in booking tickets to space and publicizing the company’s work more aggressively. If Blue Origin wants to dominate the space tourism market, now is as good a time as any.
Getting New Glenn off the ground
New Glenn is where the real fun starts. Like the Falcon Heavy, New Glenn is a heavy-lift rocket with a reusable first-stage booster, intended to send satellites into orbit. The company is targeting this year for New Glenn’s inaugural launch.
Again, Bezos can’t do anything to speed up that timetable. But what he could do is spend more time going after customers. Right now, Blue Origin has a handful of contracts to launch commercial satellites. But it’s going to need a steady stream of missions to justify New Glenn’s existence and start making money. Now would be a good time for Bezos to put those billionaire connections to use.
Satellites, satellites, satellites
And there ought to be plenty of customers who are interested. It’s cheaper than ever to build a satellite. We can make them lighter and more compact than ever before, so it’s far easier to send them into space.
When New Glenn starts flying, it ought to take a cue from SpaceX and consider ride-share missions that launch dozens or even hundreds of payloads into orbit at once. Leadership might want to start preparing such a strategy if it hopes to be a strong player in the launch provider market.
Project Kuiper
Speaking of satellites, we’re poised to see Blue Origin launching a lot more of its own payloads into orbit once New Glenn can fly. Introducing Project Kuiper: an Amazon spinoff that wants to set up a satellite constellation to provide high-speed internet to people around the world. Sounds familiar, right?
While Kuiper’s proposed 3,236-satellite constellation will be far less than the 12,000 Starlink satellites SpaceX is planning to launch, that’s still a hefty number. And perhaps Bezos can use Kuiper’s late arrival to avoid SpaceX’s mistakes with Starlink—namely, not disrupting astronomy around the world, and finding ways to manage all that orbital congestion to allay fears about collisions that could turn Earth’s orbit into dangerous minefield. While we can expect Blue Origin to play a big role in Kuiper satellite launches, Bezos has said that he’s open to using other rockets if needed, so now might also be a good time to see what’s available.
Blue Moon and Artemis
Blue Origin doesn’t just wanna stick to Earth’s orbit. It wants to go to the moon. And it wants to help NASA get there too. One of the company’s biggest projects is Blue Moon, a lunar lander that is supposed to carry cargo as well as people. Blue Origin is working with Lockheed Martin, Northrop Grumman, and Draper on a larger concept that they say NASA could use to safely take astronauts to the surface under its Artemis program. Parts of the system would be reusable, and should integrate well with NASA’s Gateway space station in lunar orbit.
The Blue Origin–led proposal seems better positioned to be selected by NASA than SpaceX’s (though Dynetics has also impressed the agency). But NASA under the Biden administration has delayed selection of a lunar lander as it reevaluates the Artemis program’s timetable and 2024 target for a moon mission.
This is good! It gives Blue Origin more time to properly test Blue Moon, work more closely with its partners on the project, and perhaps find other ways to build on these technologies for other applications.
Engine-neering
Lastly, one of Blue Origin’s biggest strengths has been its rocket engines, particularly the BE-4. Every New Glenn rocket will use the BE-4 engine, and so will United Launch Alliance’s upcoming Vulcan rocket (you don’t always see a rocket company turn to its competitor for parts). The engine will be going into space later this year for the first time, either on Vulcan or on New Glenn.
Once again, Bezos could play a bigger role in getting other aerospace companies to start incorporating BE-4 more widely in their own systems.
The technology would likely be used first on infants born at 22 or 23 weeks who don’t have many other options. “You don’t want to put an infant on this device who would otherwise do well with conventional therapy,” Mychaliska says. At 22 weeks gestation, babies are tiny, often weighing less than a pound. And their lungs are still developing. When researchers looked at babies born between 2013 and 2018, survival among those who were resuscitated at 22 weeks was 30%. That number rose to nearly 56% at 23 weeks. And babies born at that stage who do survive have an increased risk of neurodevelopmental problems, cerebral palsy, mobility problems, hearing impairments, and other disabilities.
Selecting the right participants will be tricky. Some experts argue that gestational age shouldn’t be the only criteria. One complicating factor is that prognosis varies widely from center to center, and it’s improving as hospitals learn how best to treat these preemies. At the University of Iowa Stead Family Children’s Hospital, for example, survival rates are much higher than average: 64% for babies born at 22 weeks. They’ve even managed to keep a handful of infants born at 21 weeks alive. “These babies are not a hopeless case. They very much can survive. They very much can thrive if you are managing them appropriately,” says Brady Thomas, a neonatologist at Stead. “Are you really going to make that much of a bigger impact by adding in this technology, and what risks might exist to those patients as you’re starting to trial it?”
Prognosis also varies widely from baby to baby depending on a variety of factors. “The girls do better than the boys. The bigger ones do better than the smaller ones,” says Mark Mercurio, a neonatologist and pediatric bioethicist at the Yale School of Medicine. So “how bad does the prognosis with current therapy need to be to justify use of an artificial womb?” That’s a question Mercurio would like to see answered.
What are the risks?
One ever-present concern in the tiniest babies is brain bleeds. “That’s due to a number of factors—a combination of their brain immaturity, and in part associated with the treatment that we provide,” Mychaliska says. Babies in an artificial womb would need to be on a blood thinner to prevent clots from forming where the tubes enter the body. “I believe that places a premature infant at very high risk for brain bleeding,” he says.
And it’s not just about the baby. To be eligible for EXTEND, infants must be delivered via cesarean section, which puts the pregnant person at higher risk for infection and bleeding. Delivery via a C-section can also have an impact on future pregnancies.
So if it works, could babies be grown entirely outside the womb?
Not anytime soon. Maybe not ever. In a paper published in 2022, Flake and his colleagues called this scenario “a technically and developmentally naive, yet sensationally speculative, pipe dream.” The problem is twofold. First, fetal development is a carefully choreographed process that relies on chemical communication between the pregnant parent’s body and the fetus. Even if researchers understood all the factors that contribute to fetal development—and they don’t—there’s no guarantee they could recreate those conditions.
The second issue is size. The artificial womb systems being developed require doctors to insert a small tube into the infant’s umbilical cord to deliver oxygenated blood. The smaller the umbilical cord, the more difficult this becomes.
What are the ethical concerns?
In the near term, there are concerns about how to ensure that researchers are obtaining proper informed consent from parents who may be desperate to save their babies. “This is an issue that comes up with lots of last-chance therapies,” says Vardit Ravitsky, a bioethicist and president of the Hastings Center, a bioethics research institute.
Last week, Elon Musk made the bold assertion that sticking electrodes in people’s heads is going to lead to a huge increase in the rate of data transfer out of, and into, human brains.
The occasion of Musk’s post was the announcement by Neuralink, his brain-computer interface company, that it was officially seeking the first volunteer to receive an implant that contains more than twice the number of electrodes than previous versions to collect more data from more nerve cells.
The entrepreneur mentioned a long-term goal of vastly increasing “bandwidth” between people, or people and machines, by a factor of 1,000 or more. But what does he mean, and is it even possible? Read the full story.
—Antonio Regalado
This story is from The Checkup, MIT Technology Review’s weekly biotech newsletter. Sign up to receive it in your inbox every Thursday.
Everything you need to know about artificial wombs
Earlier this month, US Food and Drug Administration advisors met to discuss how to move research on artificial wombs from animals into humans.
These medical devices are designed to give extremely premature infants a bit more time to develop in a womb-like environment before entering the outside world. They have been tested with hundreds of lambs (and some piglets), but animal models can’t fully predict how the technology will work for humans.
The reason we can’t just wish away or “fix” complexity is that every solution—whether it’s a technology or methodology—redistributes complexity in some way. Solutions reorganize problems. When microservices emerged (a software architecture approach where an application or system is composed of many smaller parts), they seemingly solved many of the maintenance and development challenges posed by monolithic architectures (where the application is one single interlocking system). However, in doing so microservices placed new demands on engineering teams; they require greater maturity in terms of practices and processes. This is one of the reasons why we cautioned people against what we call “microservice envy” in a 2018 edition of the Technology Radar, with CTO Rebecca Parsons writing that microservices would never be recommended for adoption on Technology Radar because “not all organizations are microservices-ready.” We noticed there was a tendency to look to adopt microservices simply because it was fashionable.
This doesn’t mean the solution is poor or defective. It’s more that we need to recognize the solution is a tradeoff. At Thoughtworks, we’re fond of saying “it depends” when people ask questions about the value of a certain technology or approach. It’s about how it fits with your organization’s needs and, of course, your ability to manage its particular demands. This is an example of essential complexity in tech—it’s something that can’t be removed and which will persist however much you want to get to a level of simplicity you find comfortable.
In terms of microservices, we’ve noticed increasing caution about rushing to embrace this particular architectural approach. Some of our colleagues even suggested the term “monolith revivalists” to describe those turning away from microservices back to monolithic software architecture. While it’s unlikely that the software world is going to make a full return to monoliths, frameworks like Spring Modulith—a framework that helps developers structure code in such a way that it becomes easier to break apart a monolith into smaller microservices when needed—suggest that practitioners are becoming more keenly aware of managing the tradeoffs of different approaches to building and maintaining software.
Supporting practitioners with concepts and tools
Because technical solutions have a habit of reorganizing complexity, we need to carefully attend to how this complexity is managed. Failing to do so can have serious implications for the productivity and effectiveness of engineering teams. At Thoughtworks we have a number of concepts and approaches that we use to manage complexity. Sensible defaults, for instance, are starting points for a project or piece of work. They’re not things that we need to simply embrace as a rule, but instead practices and tools that we collectively recognize are effective for most projects. They give individuals and teams a baseline to make judgements about what might be done differently.
One of the benefits of sensible defaults is that they can guard you against the allure of novelty and hype. As interesting or exciting as a new technology might be, sensible defaults can anchor you in what matters to you. This isn’t to say that new technologies like generative AI shouldn’t be treated with enthusiasm and excitement—some of our teams have been experimenting with these tools and seen impressive results—but instead that adopting new tools needs to be done in a way that properly integrates with the way you work and what you want to achieve. Indeed, there are a wealth of approaches to GenAI, from high profile tools like ChatGPT to self-hosted LLMs. Using GenAI effectively is as much a question of knowing the right way to implement for you and your team as it is about technical expertise.
Interestingly, the tools that can help us manage complexity aren’t necessarily new. One thing that came up in the latest edition of Technology Radar was something called risk-based failure modeling, a process used to understand the impact, likelihood and ability of detecting the various ways that a system can fail. This has origins in failure modes and effects analysis (FMEA), a practice that dates back to the period following World War II, used in complex engineering projects in fields such as aerospace. This signals that there are some challenges that endure; while new solutions will always emerge to combat them, we should also be comfortable looking to the past for tools and techniques.
Learning to live with complexity
McKinsey’s argument that the productivity of development teams can be successfully measured caused a stir across the software engineering landscape. While having the right metrics in place is certainly important, prioritizing productivity in our thinking can cause more problems than it solves when it comes to complex systems and an ever-changing landscape of solutions. Technology Radar called this out with an edition with the theme, “How productive is measuring productivity?”This highlighted the importance of focusing on developer experience with the help of tools like DX DevEx 360.
Focusing on productivity in the way McKinsey suggests can cause us to mistakenly see coding as the “real” work of software engineering, overlooking things like architectural decisions, tests, security analysis, and performance monitoring. This is risky—organizations that adopt such a view will struggle to see tangible benefits from their digital projects. This is why the key challenge in software today is embracing complexity; not treating it as something to be minimized at all costs but a challenge that requires thoughtfulness in processes, practices, and governance. The key question is whether the industry realizes this.
This content was produced by Thoughtworks. It was not written by MIT Technology Review’s editorial staff.
