Xenobots, tiny living machines, can duplicate themselves.
Strange and complex behavior of frog cell blobs
A xenobot “parent,” shaped like a hungry Pac-Man (shown in red false color), created an “offspring” xenobot (green sphere) by gathering loose frog cells in its opening.
Tiny “living machines” made of frog cells can make copies of themselves. This newly discovered renewal mechanism may help create self-renewing biological machines.
According to Kirstin Petersen, an electrical and computer engineer at Cornell University who studies groups of robots, “this is an extremely exciting breakthrough.” She says self-replicating robots are a big step toward human-free systems.
Researchers described the behavior of xenobots earlier this year (SN: 3/31/21). Small clumps of skin stem cells from frog embryos knitted themselves into small spheres and started moving. Cilia, or cellular extensions, powered the xenobots around their lab dishes.
The findings are published in the Proceedings of the National Academy of Sciences on Dec. 7. The xenobots can gather loose frog cells into spheres, which then form xenobots.
The researchers call this type of movement-induced reproduction kinematic self-replication. The study's coauthor, Douglas Blackiston of Tufts University in Medford, Massachusetts, and Harvard University, says this is typical. For example, sexual reproduction requires parental sperm and egg cells. Sometimes cells split or budded off from a parent.
“This is unique,” Blackiston says. These xenobots “find loose parts in the environment and cobble them together.” This second generation of xenobots can move like their parents, Blackiston says.
The researchers discovered that spheroid xenobots could only produce one more generation before dying out. The original xenobots' shape was predicted by an artificial intelligence program, allowing for four generations of replication.
A C shape, like an openmouthed Pac-Man, was predicted to be a more efficient progenitor. When improved xenobots were let loose in a dish, they began scooping up loose cells into their gaping “mouths,” forming more sphere-shaped bots (see image below). As many as 50 cells clumped together in the opening of a parent to form a mobile offspring. A xenobot is made up of 4,000–6,000 frog cells.
Petersen likes the Xenobots' small size. “The fact that they were able to do this at such a small scale just makes it even better,” she says. Miniature xenobots could sculpt tissues for implantation or deliver therapeutics inside the body.
Beyond the xenobots' potential jobs, the research advances an important science, says study coauthor and Tufts developmental biologist Michael Levin. The science of anticipating and controlling the outcomes of complex systems, he says.
“No one could have predicted this,” Levin says. “They regularly surprise us.” Researchers can use xenobots to test the unexpected. “This is about advancing the science of being less surprised,” Levin says.
More on Science
Sam Warain
3 years ago
Sam Altman, CEO of Open AI, foresees the next trillion-dollar AI company
“I think if I had time to do something else, I would be so excited to go after this company right now.”
Sam Altman, CEO of Open AI, recently discussed AI's present and future.
Open AI is important. They're creating the cyberpunk and sci-fi worlds.
They use the most advanced algorithms and data sets.
GPT-3...sound familiar? Open AI built most copyrighting software. Peppertype, Jasper AI, Rytr. If you've used any, you'll be shocked by the quality.
Open AI isn't only GPT-3. They created DallE-2 and Whisper (a speech recognition software released last week).
What will they do next? What's the next great chance?
Sam Altman, CEO of Open AI, recently gave a lecture about the next trillion-dollar AI opportunity.
Who is the organization behind Open AI?
Open AI first. If you know, skip it.
Open AI is one of the earliest private AI startups. Elon Musk, Greg Brockman, and Rebekah Mercer established OpenAI in December 2015.
OpenAI has helped its citizens and AI since its birth.
They have scary-good algorithms.
Their GPT-3 natural language processing program is excellent.
The algorithm's exponential growth is astounding. GPT-2 came out in November 2019. May 2020 brought GPT-3.
Massive computation and datasets improved the technique in just a year. New York Times said GPT-3 could write like a human.
Same for Dall-E. Dall-E 2 was announced in April 2022. Dall-E 2 won a Colorado art contest.
Open AI's algorithms challenge jobs we thought required human innovation.
So what does Sam Altman think?
The Present Situation and AI's Limitations
During the interview, Sam states that we are still at the tip of the iceberg.
So I think so far, we’ve been in the realm where you can do an incredible copywriting business or you can do an education service or whatever. But I don’t think we’ve yet seen the people go after the trillion dollar take on Google.
He's right that AI can't generate net new human knowledge. It can train and synthesize vast amounts of knowledge, but it simply reproduces human work.
“It’s not going to cure cancer. It’s not going to add to the sum total of human scientific knowledge.”
But the key word is yet.
And that is what I think will turn out to be wrong that most surprises the current experts in the field.
Reinforcing his point that massive innovations are yet to come.
But where?
The Next $1 Trillion AI Company
Sam predicts a bio or genomic breakthrough.
There’s been some promising work in genomics, but stuff on a bench top hasn’t really impacted it. I think that’s going to change. And I think this is one of these areas where there will be these new $100 billion to $1 trillion companies started, and those areas are rare.
Avoid human trials since they take time. Bio-materials or simulators are suitable beginning points.
AI may have a breakthrough. DeepMind, an OpenAI competitor, has developed AlphaFold to predict protein 3D structures.
It could change how we see proteins and their function. AlphaFold could provide fresh understanding into how proteins work and diseases originate by revealing their structure. This could lead to Alzheimer's and cancer treatments. AlphaFold could speed up medication development by revealing how proteins interact with medicines.
Deep Mind offered 200 million protein structures for scientists to download (including sustainability, food insecurity, and neglected diseases).
Being in AI for 4+ years, I'm amazed at the progress. We're past the hype cycle, as evidenced by the collapse of AI startups like C3 AI, and have entered a productive phase.
We'll see innovative enterprises that could replace Google and other trillion-dollar companies.
What happens after AI adoption is scary and unpredictable. How will AGI (Artificial General Intelligence) affect us? Highly autonomous systems that exceed humans at valuable work (Open AI)
My guess is that the things that we’ll have to figure out are how we think about fairly distributing wealth, access to AGI systems, which will be the commodity of the realm, and governance, how we collectively decide what they can do, what they don’t do, things like that. And I think figuring out the answer to those questions is going to just be huge. — Sam Altman CEO
Nojus Tumenas
3 years ago
NASA: Strange Betelgeuse Explosion Just Took Place
Orion's red supergiant Betelgeuse erupted. This is astronomers' most magnificent occurrence.
Betelgeuse, a supergiant star in Orion, garnered attention in 2019 for its peculiar appearance. It continued to dim in 2020.
The star was previously thought to explode as a supernova. Studying the event has revealed what happened to Betelgeuse since it happened.
Astronomers saw that the star released a large amount of material, causing it to lose a section of its surface.
They have never seen anything like this and are unsure what caused the star to release so much material.
According to Harvard-Smithsonian Center for Astrophysics astrophysicist Andrea Dupre, astronomers' data reveals an unexplained mystery.
They say it's a new technique to examine star evolution. The James Webb telescope revealed the star's surface features.
Corona flares are stellar mass ejections. These eruptions change the Sun's outer atmosphere.
This could affect power grids and satellite communications if it hits Earth.
Betelgeuse's flare ejected four times more material than the Sun's corona flare.
Astronomers have monitored star rhythms for 50 years. They've seen its dimming and brightening cycle start, stop, and repeat.
Monitoring Betelgeuse's pulse revealed the eruption's power.
Dupre believes the star's convection cells are still amplifying the blast's effects, comparing it to an imbalanced washing machine tub.
The star's outer layer has returned to normal, Hubble data shows. The photosphere slowly rebuilds its springy surface.
Dupre noted the star's unusual behavior. For instance, it’s causing its interior to bounce.
This suggests that the mass ejections that caused the star's surface to lose mass were two separate processes.
Researchers hope to better understand star mass ejection with the James Webb Space Telescope.
DANIEL CLERY
3 years ago
Can space-based solar power solve Earth's energy problems?
Better technology and lower launch costs revive science-fiction tech.
Airbus engineers showed off sustainable energy's future in Munich last month. They captured sunlight with solar panels, turned it into microwaves, and beamed it into an airplane hangar, where it lighted a city model. The test delivered 2 kW across 36 meters, but it posed a serious question: Should we send enormous satellites to capture solar energy in space? In orbit, free of clouds and nighttime, they could create power 24/7 and send it to Earth.
Airbus engineer Jean-Dominique Coste calls it an engineering problem. “But it’s never been done at [large] scale.”
Proponents of space solar power say the demand for green energy, cheaper space access, and improved technology might change that. Once someone invests commercially, it will grow. Former NASA researcher John Mankins says it might be a trillion-dollar industry.
Myriad uncertainties remain, including whether beaming gigawatts of power to Earth can be done efficiently and without burning birds or people. Concept papers are being replaced with ground and space testing. The European Space Agency (ESA), which supported the Munich demo, will propose ground tests to member nations next month. The U.K. government offered £6 million to evaluate innovations this year. Chinese, Japanese, South Korean, and U.S. agencies are working. NASA policy analyst Nikolai Joseph, author of an upcoming assessment, thinks the conversation's tone has altered. What formerly appeared unattainable may now be a matter of "bringing it all together"
NASA studied space solar power during the mid-1970s fuel crunch. A projected space demonstration trip using 1970s technology would have cost $1 trillion. According to Mankins, the idea is taboo in the agency.
Space and solar power technology have evolved. Photovoltaic (PV) solar cell efficiency has increased 25% over the past decade, Jones claims. Telecoms use microwave transmitters and receivers. Robots designed to repair and refuel spacecraft might create solar panels.
Falling launch costs have boosted the idea. A solar power satellite large enough to replace a nuclear or coal plant would require hundreds of launches. ESA scientist Sanjay Vijendran: "It would require a massive construction complex in orbit."
SpaceX has made the idea more plausible. A SpaceX Falcon 9 rocket costs $2600 per kilogram, less than 5% of what the Space Shuttle did, and the company promised $10 per kilogram for its giant Starship, slated to launch this year. Jones: "It changes the equation." "Economics rules"
Mass production reduces space hardware costs. Satellites are one-offs made with pricey space-rated parts. Mars rover Perseverance cost $2 million per kilogram. SpaceX's Starlink satellites cost less than $1000 per kilogram. This strategy may work for massive space buildings consisting of many identical low-cost components, Mankins has long contended. Low-cost launches and "hypermodularity" make space solar power economical, he claims.
Better engineering can improve economics. Coste says Airbus's Munich trial was 5% efficient, comparing solar input to electricity production. When the Sun shines, ground-based solar arrays perform better. Studies show space solar might compete with existing energy sources on price if it reaches 20% efficiency.
Lighter parts reduce costs. "Sandwich panels" with PV cells on one side, electronics in the middle, and a microwave transmitter on the other could help. Thousands of them build a solar satellite without heavy wiring to move power. In 2020, a team from the U.S. Naval Research Laboratory (NRL) flew on the Air Force's X-37B space plane.
NRL project head Paul Jaffe said the satellite is still providing data. The panel converts solar power into microwaves at 8% efficiency, but not to Earth. The Air Force expects to test a beaming sandwich panel next year. MIT will launch its prototype panel with SpaceX in December.
As a satellite orbits, the PV side of sandwich panels sometimes faces away from the Sun since the microwave side must always face Earth. To maintain 24-hour power, a satellite needs mirrors to keep that side illuminated and focus light on the PV. In a 2012 NASA study by Mankins, a bowl-shaped device with thousands of thin-film mirrors focuses light onto the PV array.
International Electric Company's Ian Cash has a new strategy. His proposed satellite uses enormous, fixed mirrors to redirect light onto a PV and microwave array while the structure spins (see graphic, above). 1 billion minuscule perpendicular antennas act as a "phased array" to electronically guide the beam toward Earth, regardless of the satellite's orientation. This design, argues Cash, is "the most competitive economically"
If a space-based power plant ever flies, its power must be delivered securely and efficiently. Jaffe's team at NRL just beamed 1.6 kW over 1 km, and teams in Japan, China, and South Korea have comparable attempts. Transmitters and receivers lose half their input power. Vijendran says space solar beaming needs 75% efficiency, "preferably 90%."
Beaming gigawatts through the atmosphere demands testing. Most designs aim to produce a beam kilometers wide so every ship, plane, human, or bird that strays into it only receives a tiny—hopefully harmless—portion of the 2-gigawatt transmission. Receiving antennas are cheap to build but require a lot of land, adds Jones. You could grow crops under them or place them offshore.
Europe's public agencies currently prioritize space solar power. Jones: "There's a devotion you don't see in the U.S." ESA commissioned two solar cost/benefit studies last year. Vijendran claims it might match ground-based renewables' cost. Even at a higher price, equivalent to nuclear, its 24/7 availability would make it competitive.
ESA will urge member states in November to fund a technical assessment. If the news is good, the agency will plan for 2025. With €15 billion to €20 billion, ESA may launch a megawatt-scale demonstration facility by 2030 and a gigawatt-scale facility by 2040. "Moonshot"
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Bastian Hasslinger
3 years ago
Before 2021, most startups had excessive valuations. It is currently causing issues.
Higher startup valuations are often favorable for all parties. High valuations show a business's potential. New customers and talent are attracted. They earn respect.
Everyone benefits if a company's valuation rises.
Founders and investors have always been incentivized to overestimate a company's value.
Post-money valuations were inflated by 2021 market expectations and the valuation model's mechanisms.
Founders must understand both levers to handle a normalizing market.
2021, the year of miracles
2021 must've seemed miraculous to entrepreneurs, employees, and VCs. Valuations rose, and funding resumed after the first Covid-19 epidemic caution.
In 2021, VC investments increased from $335B to $643B. 518 new worldwide unicorns vs. 134 in 2020; 951 US IPOs vs. 431.
Things can change quickly, as 2020-21 showed.
Rising interest rates, geopolitical developments, and normalizing technology conditions drive down share prices and tech company market caps in 2022. Zoom, the poster-child of early lockdown success, is down 37% since 1st Jan.
Once-inflated valuations can become a problem in a normalizing market, especially for founders, employees, and early investors.
the reason why startups are always overvalued
To see why inflated valuations are a problem, consider one of its causes.
Private company values only fluctuate following a new investment round, unlike publicly-traded corporations. The startup's new value is calculated simply:
(Latest round share price) x (total number of company shares)
This is the industry standard Post-Money Valuation model.
Let’s illustrate how it works with an example. If a VC invests $10M for 1M shares (at $10/share), and the company has 10M shares after the round, its Post-Money Valuation is $100M (10/share x 10M shares).
This approach might seem like the most natural way to assess a business, but the model often unintentionally overstates the underlying value of the company even if the share price paid by the investor is fair. All shares aren't equal.
New investors in a corporation will always try to minimize their downside risk, or the amount they lose if things go wrong. New investors will try to negotiate better terms and pay a premium.
How the value of a struggling SpaceX increased
SpaceX's 2008 Series D is an example. Despite the financial crisis and unsuccessful rocket launches, the company's Post-Money Valuation was 36% higher after the investment round. Why?
Series D SpaceX shares were protected. In case of liquidation, Series D investors were guaranteed a 2x return before other shareholders.
Due to downside protection, investors were willing to pay a higher price for this new share class.
The Post-Money Valuation model overpriced SpaceX because it viewed all the shares as equal (they weren't).
Why entrepreneurs, workers, and early investors stand to lose the most
Post-Money Valuation is an effective and sufficient method for assessing a startup's valuation, despite not taking share class disparities into consideration.
In a robust market, where the firm valuation will certainly expand with the next fundraising round or exit, the inflated value is of little significance.
Fairness endures. If a corporation leaves at a greater valuation, each stakeholder will receive a proportional distribution. (i.e., 5% of a $100M corporation yields $5M).
SpaceX's inherent overvaluation was never a problem. Had it been sold for less than its Post-Money Valuation, some shareholders, including founders, staff, and early investors, would have seen their ownership drop.
The unforgiving world of 2022
In 2022, founders, employees, and investors who benefited from inflated values will face below-valuation exits and down-rounds.
For them, 2021 will be a curse, not a blessing.
Some tech giants are worried. Klarna's valuation fell from $45B (Oct 21) to $30B (Jun 22), Canvas from $40B to $27B, and GoPuffs from $17B to $8.3B.
Shazam and Blue Apron have to exit or IPO at a cheaper price. Premium share classes are protected, while others receive less. The same goes for bankrupts.
Those who continue at lower valuations will lose reputation and talent. When their value declines by half, generous employee stock options become less enticing, and their ability to return anything is questioned.
What can we infer about the present situation?
Such techniques to enhance your company's value or stop a normalizing market are fiction.
The current situation is a painful reminder for entrepreneurs and a crucial lesson for future firms.
The devastating market fall of the previous six months has taught us one thing:
Keep in mind that any valuation is speculative. Money Post A startup's valuation is a highly simplified approximation of its true value, particularly in the early phases when it lacks significant income or a cutting-edge product. It is merely a projection of the future and a hypothetical meter. Until it is achieved by an exit, a valuation is nothing more than a number on paper.
Assume the value of your company is lower than it was in the past. Your previous valuation might not be accurate now due to substantial changes in the startup financing markets. There is little reason to think that your company's value will remain the same given the 50%+ decline in many newly listed IT companies. Recognize how the market situation is changing and use caution.
Recognize the importance of the stake you hold. Each share class has a unique value that varies. Know the sort of share class you own and how additional contractual provisions affect the market value of your security. Frameworks have been provided by Metrick and Yasuda (Yale & UC) and Gornall and Strebulaev (Stanford) for comprehending the terms that affect investors' cash-flow rights upon withdrawal. As a result, you will be able to more accurately evaluate your firm and determine the worth of each share class.
Be wary of approving excessively protective share terms.
The trade-offs should be considered while negotiating subsequent rounds. Accepting punitive contractual terms could first seem like a smart option in order to uphold your inflated worth, but you should proceed with caution. Such provisions ALWAYS result in misaligned shareholders, with common shareholders (such as you and your staff) at the bottom of the list.
Muthinja
3 years ago
Why don't you relaunch my startup projects?
Open to ideas or acquisitions
Failure is an unavoidable aspect of life, yet many recoil at the word.
I've worked on unrelated startup projects. This is a list of products I developed (often as the tech lead or co-founder) and why they failed to launch.
Chess Bet (Betting)
As a chess player who plays 5 games a day and has an ELO rating of 2100, I tried to design a chess engine to rival stockfish and Houdini.
While constructing my chess engine, my cofounder asked me about building a p2p chess betting app. Chess Bet. There couldn't be a better time.
Two people in different locations could play a staked game. The winner got 90% of the bet and we got 10%. The business strategy was clear, but our mini-launch was unusual.
People started employing the same cheat engines I mentioned, causing user churn and defaming our product.
It was the first programming problem I couldn't solve after building a cheat detection system based on player move strengths and prior games. Chess.com, the most famous online chess software, still suffers from this.
We decided to pivot because we needed an expensive betting license.
We relaunched as Chess MVP after deciding to focus on chess learning. A platform for teachers to create chess puzzles and teach content. Several chess students used our product, but the target market was too tiny.
We chose to quit rather than persevere or pivot.
BodaCare (Insure Tech)
‘BodaBoda’ in Swahili means Motorcycle. My Dad approached me in 2019 (when I was working for a health tech business) about establishing an Insurtech/fintech solution for motorbike riders to pay for insurance using SNPL.
We teamed up with an underwriter to market motorcycle insurance. Once they had enough premiums, they'd get an insurance sticker in the mail. We made it better by splitting the cover in two, making it more reasonable for motorcyclists struggling with lump-sum premiums.
Lack of capital and changing customer behavior forced us to close, with 100 motorcyclists paying 0.5 USD every day. Our unit econ didn't make sense, and CAC and retention capital only dug us deeper.
Circle (Social Networking)
Having learned from both product failures, I began to understand what worked and what didn't. While reading through Instagram, an idea struck me.
Suppose social media weren't virtual.
Imagine meeting someone on your way home. Like-minded person
People were excited about social occasions after covid restrictions were eased. Anything to escape. I just built a university student-popular experiences startup. Again, there couldn't be a better time.
I started the Android app. I launched it on Google Beta and oh my! 200 people joined in two days.
It works by signaling if people are in a given place and allowing users to IM in hopes of meeting up in near real-time. Playstore couldn't deploy the app despite its success in beta for unknown reasons. I appealed unsuccessfully.
My infrastructure quickly lost users because I lacked funding.
In conclusion
This essay contains many failures, some of which might have been avoided and others not, but they were crucial learning points in my startup path.
If you liked any idea, I have the source code on Github.
Happy reading until then!
Tom Connor
3 years ago
12 mental models that I use frequently
https://tomconnor.me/wp-content/uploads/2021/08/10x-Engineer-Mental-Models.pdf
I keep returning to the same mental models and tricks after writing and reading about a wide range of topics.
Top 12 mental models
12.
Survival bias - We perceive the surviving population as remarkable, yet they may have gotten there through sheer grit.
Survivorship bias affects us in many situations. Our retirement fund; the unicorn business; the winning team. We often study and imitate the last one standing. This can lead to genuine insights and performance improvements, but it can also lead us astray because the leader may just be lucky.
11.
The Helsinki Bus Theory - How to persevere Buss up!
Always display new work, and always be compared to others. Why? Easy. Keep riding. Stay on the fucking bus.
10.
Until it sticks… Turning up every day… — Artists teach engineers plenty. Quality work over a career comes from showing up every day and starting.
9.
WRAP decision making process (Heath Brothers)
Decision-making WRAP Model:
W — Widen your Options
R — Reality test your assumptions
A — Attain Distance
P — Prepare to be wrong or Right
8.
Systems for knowledge worker excellence - Todd Henry and Cal Newport write about techniques knowledge workers can employ to build a creative rhythm and do better work.
Todd Henry's FRESH framework:
Focus: Keep the start in mind as you wrap up.
Relationships: close a loop that's open.
Pruning is an energy.
Set aside time to be inspired by stimuli.
Hours: Spend time thinking.
7.
BBT is learning from mistakes. Science has transformed the world because it constantly updates its theories in light of failures. Complexity guarantees failure. Do we learn or self-justify?
6.
The OODA Loop - Competitive advantage
O: Observe: collect the data. Figure out exactly where you are, what’s happening.
O: Orient: analyze/synthesize the data to form an accurate picture.
D: Decide: select an action from possible options
A: Action: execute the action, and return to step (1)
Boyd's approach indicates that speed and agility are about information processing, not physical reactions. They form feedback loops. More OODA loops improve speed.
5.
Leaders who try to impose order in a complex situation fail; those who set the stage, step back, and allow patterns to develop win.
https://vimeo.com/640941172?embedded=true&source=vimeo_logo&owner=11999906
4.
Information Gap - The discrepancy between what we know and what we would like to know
Gap in Alignment - What individuals actually do as opposed to what we wish them to do
Effects Gap - the discrepancy between our expectations and the results of our actions
3.
Theory of Constraints — The Goal - To maximize system production, maximize bottleneck throughput.
Goldratt creates a five-step procedure:
Determine the restriction
Improve the restriction.
Everything else should be based on the limitation.
Increase the restriction
Go back to step 1 Avoid letting inertia become a limitation.
Any non-constraint improvement is an illusion.
2.
Serendipity and the Adjacent Possible - Why do several amazing ideas emerge at once? How can you foster serendipity in your work?
You need specialized abilities to reach to the edge of possibilities, where you can pursue exciting tasks that will change the world. Few people do it since it takes a lot of hard work. You'll stand out if you do.
Most people simply lack the comfort with discomfort required to tackle really hard things. At some point, in other words, there’s no way getting around the necessity to clear your calendar, shut down your phone, and spend several hard days trying to make sense of the damn proof.
1.
Boundaries of failure - Rasmussen's accident model.
Rasmussen modeled this. It has economic, workload, and performance boundaries.
The economic boundary is a company's profit zone. If the lights are on, you're within the economic boundaries, but there's pressure to cut costs and do more.
Performance limit reflects system capacity. Taking shortcuts is a human desire to minimize work. This is often necessary to survive because there's always more labor.
Both push operating points toward acceptable performance. Personal or process safety, or equipment performance.
If you exceed acceptable performance, you'll push back, typically forcefully.