Both Booster and Dragon spacecraft are flight proven for today’s Crew-2 flight to the ISS. NΛSΛ chooses flight-proven spacecraft and booster for its most precious missions. Dragon Pilot Megan McArthur is sitting in the very same seat that her husband Bob Behnken sat for the SpaceX DM-2 mission 11 months ago. Thank you for helping humanity raise its aspirations and dreams!
P.S. many years ago, when reusable boosters were an audacious dream, I heard them described as “used”, as in a used car. No, no, we should call them “flight proven” and I wagered that the long term data would show them to be safer than a first flight. “Would you want to be on the very first flight of a new airplane coming off the line?” I asked. The moniker became a meme.
By a truly unbelievable coincidence, I was recently out for a walk when I saw a small package fall off a truck ahead of me. As I got closer, the dull enterprise typeface slowly came into focus: Cellebrite. Inside, we found the latest versions of the Cellebrite software, a hardware dongle designed to prevent piracy (tells you something about their customers I guess!), and a bizarrely large number of cable adapters.
By including a specially formatted but otherwise innocuous file in an app on a device that is then scanned by Cellebrite, it’s possible to execute code that modifies not just the Cellebrite report being created in that scan, but also all previous and future generated Cellebrite reports from all previously scanned devices and all future scanned devices in any arbitrary way (inserting or removing text, email, photos, contacts, files, or any other data), with no detectable timestamp changes or checksum failures. This could even be done at random, and would seriously call the data integrity of Cellebrite’s reports into question.
Any app could contain such a file, and until Cellebrite is able to accurately repair all vulnerabilities in its software with extremely high confidence, the only remedy a Cellebrite user has is to not scan devices. In completely unrelated news, upcoming versions of Signal will be periodically fetching files to place in app storage. These files are never used for anything inside Signal and never interact with Signal software or data, but they look nice, and aesthetics are important in software. Files will only be returned for accounts that have been active installs for some time already, and only probabilistically in low % based on phone number sharding. We have a few different versions of files that we think are aesthetically pleasing, and will iterate through those slowly over time. There is no other significance to these files.
Workers at Amazon’s warehouse in Bessemer, Alabama, voted by a margin of more than 2 to 1 not to join a union. It’s a heavy blow for the Retail, Wholesale and Department Store Union, for the wider labor movement, and for the many politicians and activists who wanted the union’s push to succeed. But the workers have spoken — and all of the groups on the other side should be listening to the message. Instead, many rejected the result and attacked the process, almost as though an election is to be respected only if you win. When Republicans did that after the presidential election, they were rightly condemned. The idea that the overwhelming majority of workers in Bessemer were intimidated or bamboozled into voting against their interests — as unionization proponents have suggested — is not only implausible; it’s insulting, as though workers couldn’t possibly be so foolish to have voted against it, so they must have been coerced or tricked. Nonsense.
These are what some social scientists call “expedient friendships”—with people we might call “deal friends”—and they are probably the most common type most of us have. The average adult has 16 people they would classify as friends. Of these, 3 are “friends for life,” and 5 are people they really like. The other 8 are not people they would hang out with 1-on-1. We can logically infer that these friendships are not an end in themselves but are instrumental to some other goal, such as furthering one’s career or easing a social dynamic. Expedient friendships might be a pleasant—and certainly useful—part of life, but they don’t usually bring lasting joy and comfort. If you find that your social life is leaving you feeling a little empty and unfulfilled, it might just be that you have too many deal friends, and not enough real friends.
Almost all neuroscientists base their search—for the physical basis of memory (the engram)—on the assumption that temporal-pairing causes learning. They are dedicated to this assumption—even though, as Rescorla pointed out 50 years ago, experimental attempts to define temporal-pairing have always failed. This failure is as striking now as it was 50 years ago. Anything that gets neuroscientists to abandon the idea that temporal-pairing is a useful scientific concept is a step toward discovering the physical basis of memory. Each neuron contains billions of (almost) incomprehensibly-tiny molecular machines. Molecular biologists have developed an astonishing array of techniques for visualizing/manipulating the actions of these little machines. These techniques will allow molecular biologists to follow the machines inside this huge neuron to the engram—to the tiny machine that encodes the experience-gleaned facts so that these learned/remembered facts can inform later behavior.
Biology feels different right now. New broadly enabling technologies and tools are driving forward progress in nearly every specific field at a rapid pace. The large scale adoption and application of a powerful set of common tools has created a virtuous cycle of further technology refinement and engineering. The rate of iteration is increasing, and previously intractable problems are now within reach. While RNA-seq and MPRAs are both valuable approaches, they come with some limitations. Fundamentally, each measurement represents a single static slice of a dynamic process which is only inferred by attempting to piece together the slices. The quality of the reconstruction is limited by sampling density. What if we could measure these systems continually as they occurred in a way that didn’t require destructive sampling? Here, the fundamental idea is that “DNA is the natural medium for biological information storage, and is easily ‘read’ through sequencing.” This forms the basis for this new technology: ENGRAM (ENhancer-driven Genomic Recording of transcriptional Activity in Multiplex). The workflow of this technique is very similar to that of the MPRA introduced above, but with an important twist. Instead of destroying the cell and sequencing a ratio of barcodes, the transcription event is recorded by the insertion of a barcode into a locus of DNA in the cell via prime editing. They went further and showed that they could effectively multiplex this technique by reading out all 3 signals in response to stimulants in a single population of cells. Even more, they showed a proof-of-concept for reading out the order in which events occurred.
we need far more human challenge trials, and far less garbage people like ethicists.
In interviews, former challenge trial participants described motives for their participation that ranged from the light-hearted — several imagined it would be a fun story to tell at scientific conferences and parties — to the serious. Some spoke of altruistic motives, often shaped by personal experiences. “I spent a couple years in Africa; I was in the Peace Corps. I think for me, seeing that firsthand, and knowing that there might be some way that maybe I can be a part of figuring out whether or not we can make a vaccine for malaria definitely played a big part in it for me.”
People who don’t look any deeper than the Gini coefficient look back on the world of 1982 as the good old days, because those who got rich then didn’t get as rich. But if you dig into how they got rich, the old days don’t look so good. In 1982, 84% of the richest 100 people got rich by inheritance, extracting natural resources, or doing real estate deals. Is that really better than a world in which the richest people get rich by starting tech companies? Why are people starting so many more new companies than they used to, and why are they getting so rich from it? The answer to the first question, curiously enough, is that it’s misphrased. We shouldn’t be asking why people are starting companies, but why they’re starting companies again. In 1892, the New York Herald Tribune compiled a list of all the millionaires in America. They found 4047 of them. How many had inherited their wealth then? Only @20% — less than the proportion of heirs today. And when you investigate the sources of the new fortunes, 1892 looks even more like today. Hugh Rockoff found that “many of the richest … gained their initial edge from the new technology of mass production.”
this looks promising to change construction from a lazy, inefficient industry where most people stand around, to a much leaner, faster, 24/7 operation.
In July the Conference of Chief Justices and the Conference of State Court Administrators jointly endorsed a set of “Guiding Principles for Post-pandemic Court Technology” with a blunt message: The legal system should “move as many court processes as possible online,” and keep them there after the risk of infection passes. The pandemic, they wrote, “is not the disruption courts wanted, but it is the disruption that courts needed.”
Tenants facing eviction in Arizona and parents threatened with losing their children in Texas also proved much more likely to make their court dates when they could do so online. Likewise citizens summoned for jury duty: In Texas, 60-80% show up online. That’s 2x as many as formerly appeared in person. The trend bodes well for diversifying juries, which tend to skew white and affluent.
As these trade-offs become clearer, some initial consensus is emerging as to what virtual courts should and shouldn’t do post-pandemic. Just about everyone, even a skeptic like Douglas Hiatt, agrees that they should keep handling the routine business—from scheduling and settlement conferences to contested traffic tickets and uncontested divorces—that fills most court time.
Gregor J. Rothfuss 