Hello again! These are my latest thoughts on the areas I’m interested in. I hope you’ll enjoy learning more.
In this roundup:
What more can be said about the AI boom that began its ascent less than a year ago? A lot! The potential of AI is immense and its influence on our lives is sure to be significant. And so I’ll continue. . .
In this essay I’ll focus more on Large Language Models (LLMs), but my thoughts apply to all other AI efforts as well.
An easy way to think of it is that LLMs will soon become the “autocomplete for everything”:
What’s common to all of these visions is something we call the “sandwich” workflow. This is a three-step process. First, a human has a creative impulse, and gives the AI a prompt. The AI then generates a menu of options. The human then chooses an option, edits it, and adds any touches they like.
. . . So that’s our prediction for the near-term future of generative AI – not something that replaces humans, but something that gives them superpowers. A proverbial bicycle for the mind. Adjusting to those new superpowers will be a long, difficult trial-and-error process for both workers and companies, but as with the advent of machine tools and robots and word processors, we suspect that the final outcome will be better for most human workers than what currently exists.
There seems to be an unlimited number of areas that language prompting + completion will enable. Some are obvious: a new iteration of Google, help with writing, content generation, help with marketing copy, etc. You see many startups and tools that have already sprung up to tackle these.
Some of the real interesting applications that are incubating now will have action models as a big component. Models will have the ability to take actions like: searching the web; ordering an item; making a reservation; using a calculator; or using any other digital tool that humans are capable of using. Imagine ChatGPT being able to confirm its answers with multiple sources, or having access to all your personal records it can use to assist you.
Prompt engineers are already discovering how much you can do with the existing models, without any new advancements or manipulation of the actual base model. Even if GPT-4 or an open-source LLM from Stability.ai take years to come out, the existing tools are enough for huge changes.
The above is an idea maze I sketched out for products enabled by LLMs. The key question it starts with is “What kind of interface would the use have with the product?”
Continue reading “The New AI Epoch”
The following is a short case study on “Creator”, a cloud-based content management system I built at Mashgin, where we make visual self-checkout kiosks that use computer vision to see items so you don’t have to scan barcodes.
In the years since launch, it has given location managers the ability to customize their menus in ways they were unable to in the past. This empowers them to make frequent changes, tailoring the menu to customer needs rather than just “using the default”.
Mashgin Creator is a tool for operators to build and manage their menus, from items to discounts, schedules, and more.
Mashgin customers have been able to easily edit their checkout items in the cloud since we first launched in 2016. But when we began to design our mobile and in-person ordering app, we realized customers would need an easy way to design more complex menus, with custom item options, photos, nested categories, scheduling, and more. This is where the idea for Creator came in.
Creator is what they call in the industry a “CMS”, or content management system. Any software tool used to manage content of any type could apply.
In the food service industry, a CMS is used to manage their menu items, pricing, discounts, taxes, etc. The scope could be anywhere from an individual cafe to a nationwide chain of stores.
Most existing CMS software for food service was cumbersome to use and poorly designed. It was really just a simple layer on top of a database, allowing users to edit basic item information. Some software didn’t even allow for real-time syncing of data — any changes are “submitted” and someone behind the scenes has to deploy them to the menu.
The output of these menus is very simple: it’s just items in some nested menus, each with its own data like price, type, options, etc. But the work and consideration that has to go into building each menu is anything but simple.
It was clear that our customers needed something much better.
Believing that all the existing tools weren’t very good, we chose not to base the core design off of any other examples or prior work. Creator would be rethought from the ground up based on the needs and jobs of its users.
Continue reading “Creating Creator”
How SpaceX innovates by moving fast and blowing things up.
One of the greatest business successes over the last 20 years has been SpaceX’s rise to dominance. SpaceX now launches more rockets to orbit than any other company (or nation) in the world. They seem to move fast on every level, out executing and out innovating everyone in the industry.
Their story has been rightfully told as one of engineering brilliance and determination.
But at its core, the key their success is much simpler.
There’s a clue in this NASA report on the Commercial Crew Program:
SpaceX and Boeing have very different philosophies in terms of how they develop hardware. SpaceX focuses on rapidly iterating through a build-test-learn approach that drives modifications toward design maturity. Boeing utilizes a well-established systems engineering methodology targeted at an initial investment in engineering studies and analysis to mature the system design prior to building and testing the hardware. Each approach has advantages and disadvantages.
This is the heart of why SpaceX won. They take an iterative path.
Let’s talk about the Boeing philosophy first, which is the most common approach taken by other traditional aerospace companies. “There are basically two approaches to building complex systems like rockets: linear and iterative design,” Eric Berger writes in the book “Liftoff” about the early history of SpaceX:
The linear method begins with an initial goal, and moves through developing requirements to meet that goal, followed by numerous qualification tests of subsystems before assembling them into the major pieces of the rocket, such as its structures, propulsion, and avionics. With linear design, years are spent engineering a project before development begins. This is because it is difficult, time-consuming, and expensive to modify a design and requirements after beginning to build hardware.
I call this the “determinate path” — in trying to accomplish a goal, the path to get there is planned and fixed in advance.
Continue reading “Take the Iterative Path”The key to faster progress is increased desire for more. That’s my theory, at least.
In all the commentary on the “Great Stagnation”, much is written about the lack of progress in tech areas like transportation. Commercial airplane speeds, for example, have decreased on average since the ‘70s:
Since 1973, airplane manufacturers have innovated on margins other than speed, and as a result, commercial flight is safer and cheaper than it was 40 years ago. But commercial flight isn’t any faster—in fact, today’s flights travel at less than half the Concorde’s speed. (Airplane Speeds Have Stagnated for 40 Years, by Eli Dourado and Michael Kotrous.)
There are clearly many contributors to this. Regulation is cited in the above post and seems to be most common reason mentioned. Rising energy costs is another major one. The less-talked-about contributor is consumer demand.
Clayton Christensen’s theory on disruptive innovation shows that as average performance demanded goes up, the performance level supplied by products generally goes up faster, eventually surpassing the majority of the market.
As a technology improves, its performance surpasses most market demand, and things became “good enough” over time. Customers aren’t willing to pay more for better performance. This leaves the market open for disruptors — either on the low-end (good enough performance but cheaper), or by having better performance on a completely different metric.
Back to airline travel. Flying from NYC to LAX in 6 hours became good enough for most people. Sure, less would be better, but not at much more cost. Only high end, richer users truly needed more. So airplane makers moved on to other attributes that weren’t good enough: safety, flexibility, price.
Continue reading “To Increase Progress, Increase Desire”
There has been an increasing amount of experimentation in the philanthropic and scientific funding space over the past few years. This is good news — as I mentioned in my last post, we need better ways to fund crazy ideas.
Here’s a sampling of some of the recent efforts:
In “Illegible Medicis and Hunting for Outliers” Rohit observes that:
There are two common themes here. That’s speed and autonomy. They mostly act under the assumption (the correct assumption it would seem from a betting lens) that they can identify talent, not bug them excessively, and leave them to do their thing. Instead of imposing rules and strictures and guidelines, they focus on letting the innate megalomania do the work of focusing their research.
The academic and government driven funding models have come up against their limits in recent years (decades?). These experiments provide new methods to allocate capital to research, development, and implementation of efforts that for whatever reason aren’t amenable to the startup funding ecosystem.
Prior to World War II, support from non-government or educational institutions was the norm. Patrons like Alfred Loomis ran a lab at Tuxedo Park, hosting scientists and engineers from around the world that was integral in the creation of radar. Funding was provided by philanthropies from the likes of Carnegie and Rockefeller. Or private R&D from Edison, Bell Labs or Cold Springs Harbor Lab.
These past models are still doing well of course — HHMI, the Gates Foundation, Google X, etc. — but much more is needed to expand experimentation. The government can continue to play a valuable role, particularly as a buyer of first resort.
I’m super excited to see what comes from these orgs. A few like Fast Grants have already had some impact.
For more on the topic, see:
Cover photo by The National Cancer Institute, Unsplash.
There is as much headroom in physics and engineering for energy as there is in computation; what is stopping us is not lack of technology but lack of will and good sense. — J. Storrs Hall
There have been three industrial revolutions. The first two spanned from the late 1700s to the early 1900s and essentially created the technological world we know today. Energy, transportation, housing, and most “core” infrastructure is pretty similar now as it was at the end of this period — especially if you extend it into the 1970s. The third revolution, the “Digital Revolution”, started around this time and as anyone reading this knows has made computing and communication ubiquitous.
There were bad things that came from these revolutions: pollution, environmental destruction, war, child labor, etc. But the good overwhelmed the bad, leading to GDP per capita (”resources per person”) doing this, which we can use as a proxy for progress in a host of other areas like longer/healthier lifespan, lower child mortality, less violence, lower poverty, and more.
Wikipedia describes the potential Fourth Industrial Revolution as “…the joining of technologies like artificial intelligence, gene editing, to advanced robotics that blur the lines between the physical, digital, and biological worlds.”
These things are great, but we need more. Much more.
As just one example, it’s become abundantly clear over the past few weeks the importance of energy independence. But why don’t we already have it?
The cost of PV cells has collapsed over the past few decades. We also know it’s possible to build nuclear reactors far safer and more productive than any in the past. There should be solar panels on every home, geothermal wells in every town, and multiple nuclear fission (possibly fusion?) reactors in every state. A setup like this would lead to redundant energy at every scale, not reliant on geopolitics or over-centralization.
We should want to consume more energy, not less. (And unlike the second industrial revolution, it can be clean energy with minimal externalities.)
What else could a new industrial revolution bring? Just imagine what you’d see in a typical sci-fi movie:
Space parks/hotels/colonies, limb regeneration, flying cars, supersonic jets, same-day shipping to anywhere on Earth, self-replicating nanobots, new animal species, plants everywhere, infrastructure made out of GM trees, universal vaccines for all viruses, mobile robotic surgeons that can save lives on-location, convoys of self-driving cars, batteries with 50x current power, etc. etc.
To build these things — or even to see if they’re possible — a lot needs to change. Here’s just a few I’ve been thinking about:
If you agree with any of the above or are interested in similar ideas, here’s a few good resources I’ve enjoyed recently:
The “Singularity” in artificial intelligence is the future moment when generalized AI becomes smarter than humans. In theory this starts a feedback loop of runaway intelligence that radically changes our world in ways that are hard to predict.
Similar points exist in other industries as well. These are ultra tipping points that would lead to drastic changes in the industry and our world — changes so great we could only make very rough guesses as to what they’d be.
What are some potential examples?
Some of these tipping points look like they’re in our near future, and there’s no reason to believe any of them aren’t possible. A few of them would likely make others on the list easier. Every one of them has downsides but the upsides are massive. How exciting!
What else can be added to the above list that I forgot?
(Tipping points in brain-machine interfaces, construction and building, healthcare, etc.)
Greetings FutureBlind readers!
It’s been a while. Although I have 3 or so posts outlined and in various states of completion, life has gotten in the way. My wife and I’s first child is due in a few months (Are we in the thick of a post-Covid baby boom?) and in an act of complete lunacy this summer we started a major home renovation. This has, to put it mildly, put a damper on my free time.
Nonetheless I really wanted to write a bit and put something out there. So instead of the typical focused post, I’m doing it roundup style. Each section below is an area I follow or find interesting.
Here’s an outline of the roundup so you can jump to whichever section sounds interesting:
Getting to space is about to get a lot easier. I reviewed the reasons why in Part I. Now for the fun part: what it will lead to.
A 10x reduction in cost to orbit has already started to change things. The next 10x reduction will lead to outcomes and use cases much harder to comprehend or predict. It would have been hard for anyone in the late 1800s to predict what drastically lower costs of energy and electricity would eventually bring. Or for anyone in the 1970s to predict the consequences of abundant computing power and ubiquitous global communication (Reddit? NFTs? Protein folding?).
But we can try.
This summary is focused on some of the changes we’re likely to see in the next 5 to 20 years. A lot can happen in that time frame. For reference, it’s taken SpaceX only 19 years to accomplish what they have. But progress compounds and is exponential — especially so once a tipping point like this has been crossed. The change we’ll see in the next 20 years will dwarf that of the last 20.
(Quick note: This isn’t meant to be comprehensive. It’s a highlight of the new areas I find most interesting, and doesn’t include anything on the two biggest space segments: communication and Earth observation. Although there are plenty of interesting potentials here — like globally available high-speed internet [Starlink] or ubiquitous, near-real-time worldwide monitoring [Planet].)
The progress of SpaceX, the current leader here, was detailed in Part I. Given the Falcon 9’s low costs, it’s likely to be the preferred choice for medium-sized payloads, and even smaller payloads with rideshares.
Until now, SpaceX has self-funded their Starship super-heavy launch vehicle. That changed a few weeks ago when NASA announced that Starship had won the contract to land humans on the Moon again. This is huge. The contract will fund $2.9 billion of development costs and speed up the timeline for Starship to become human rated. With the pace of their current development, Starship is on track to become fully operational within 3 years. This should keep SpaceX the leader for heavy and super-heavy launches for some time.
When it comes to delivering humans, the other Commercial Crew competitor, Boeing, is more than a year behind after testing mishaps. Blue Origin may the next best bet for heavy-launch vehicles and a dark horse candidate given its potential funding from Jeff Bezos. There’s multiple smaller upstarts like Rocket Lab, Relativity Space or Astra at the low-end of the market, potentially moving disruptively upward. SpaceX blazed the path for these rocket companies, showing how far costs can come down, and proving that lower prices can expand market size.
Also included in this category are spaceports. Most spaceports are currently owned and operated by governments — like Kennedy Space Center at Cape Canaveral, Florida, or Vandenberg Air Force Base in California. This will start to change in tandem with the growth of commercial space.
Spaceport America in New Mexico is an example of an all-commercial spaceport, similar to most airports in that it’s owned and operated by the state. Rocket Lab built their own spaceport, Rocket Lab Launch Complex 1, in New Zealand. SpaceX’s R&D facilities in Boca Chica, Texas are now being converted into not only a spaceport, but a township to support Starship launches. Given Starship’s eventual importance, there’s no doubt this will become a hub of activity. Launches, and more importantly landings, will also take place on converted offshore oil rigs.
Most current space activity takes place in Earth orbit. As it becomes cheaper to leave the influence of Earth’s gravity, we’ll start expanding further out into the Solar System. The best staging point for this expansion isn’t spaceports on Earth — it’s the Moon and lunar orbit.
The Moon has one-sixth the gravity of Earth and no atmosphere. The means the energy (or delta-v) required to launch from its surface is much lower. The Moon also contains 600 million tons of ice, and its soil is 40-45% oxygen by mass. These raw materials can be used to produce propellants for launch, along with water and breathable oxygen — nearly 100 grams for every kilogram of soil. A Moon base is not far off in our future.
On the Moon, concepts like space elevators or skyhooks also become possible[1]. Imagine a structure — similar to piers going into the ocean — extending from the lunar surface into orbit. Satellites can be sent up the elevator into orbit and ships can “dock” at the top, where supplies can be loaded with much less energy cost.
Once other infrastructure like commercial space stations and lunar bases get set up, I think we’ll start seeing regularly scheduled launches to specific destinations. From quarterly launches to monthly, weekly, and eventually daily. (Questions to ponder: Can rockets fit in the existing intermodal shipping system? What would a new space-specific intermodal container look like?)
Continue reading “The Future of Space, Part II: The Potential”
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