Before we dive into this, I want to give a very small (and admittedly simple) overview of proteins and their significance in biological science. In short, proteins are essential building blocks of life that govern activity inside of cells. Proteins are chains of amino acids, and they take on specific shapes that are deterministic. When one amino acid connects with another, they form a specific shape that helps them carry out their intended actions.
Interestingly, these shapes are deterministic – if we know which amino acid is present and what it is connected to, we can accurately know the shape the protein will take. These shapes are not random – they appear to be guided by pure physics and the specific components available. This is vitally important to biological study, and numerous scientists are at work around the globe to further this research.
We have some methods in biological science for determining the shape of proteins, including X-ray crystallography and cryo-electron microscopy (cryo-EM); the latter is revolutionary in and of itself and has produced the most accurate protein shapes to date. Research has been ongoing since the 1950s, but has proven to be arduous and slow through the use of manual techniques. Computers have only recently been utilized as tools that help this research along.
Some readers may remember Folding@home, which was a small program users could install on their computers to help with protein folding research efforts. It was a small app that would work in the background and/or when a computer was idle. As a distributed program that was running on computers around the globe, it allowed the collective power of the internet to aid scientists as they probed this critical topic further.
John Moult, a computational biologist at the University of Maryland in College Park, founded a competition in 1994 called Critical Assessment of Structure Prediction (or CASP) to encourage research entities to put forth their techniques in the name of progress. Since then, groups have worked on protein structures that are not known publicly, and their results are compared to see who has most closely found the correct shape.
Two years ago, Google’s DeepMind outfit saw their AlphaFold program win the competition, generating results that were excitedly received. While it was using an AI-driven approach that was similar to other competitors, its deep learning algorithms would take its findings to help generate a “consensus model” of the protein’s shape. While incredible, this process hit a wall, and was unable to progress further.
John Jumper – the leader at DeepMind – then worked with his team to develop an AI network to improve its predictions. The results have proven astounding to biological science. “In some sense the problem is solved” according to Moult. CASP gives out a score to each group on a 100 point scale; most averaged a 75, while AlphaFold turned in scores near 90.
Even in places where AlphaFold doesn’t quite perform as well, the raw data is still invaluable. Mohammed AlQuraishi, a computational biologist at Columbia University in New York City and a CASP participant, remarks that, ““I think it’s fair to say this will be very disruptive to the protein-structure-prediction field. I suspect many will leave the field as the core problem has arguably been solved,” he says. “It’s a breakthrough of the first order, certainly one of the most significant scientific results of my lifetime.”
The benefits of such research are difficult to fully understand, but are incredibly exciting. Andrei Lupas, an evolutionary biologist at the Max Planck Institute for Developmental Biology in Tübingen, Germany, believes that, “It’s a game changer. This will change medicine. It will change research. It will change bioengineering. It will change everything.” AlphaFold was able to help him determine a protein structure that his lab had struggled with for ten years.
Applications could mean designing our own proteins, better drugs that are created more quickly, and the ability to find solutions to diseases through the creation of new medicines and therapies. In a world where AI could bring about amazing healthcare benefits, AlphaFold’s work could usher in a new era of study and biological understanding. It cracked a 50 year old problem; the possibilities are endless.
It will take some time for this kind of research to be applied, but scientists are eager to continue AlphaFold’s work. Demis Hassabis, DeepMind’s co-founder and chief executive, says that the company plans to make AlphaFold useful so other scientists can employ it. “I do think it’s the most significant thing we’ve done, in terms of real-world impact.”
Get all your digital organization in one place with Routine
(TECH NEWS) Routine makes note-taking and task-creating a lot easier by merging all your common processes into one productivity tool.
Your inbox can either be your best friend or your worst enemy. Without organization, important emails with tasks, notes, and meetings can become a trash pile pretty quickly. Luckily, there are a lot of tools that aim to help you improve your efficiency, and the latest to add to that list is Routine.
Routine is a productivity app that combines your tasks, notes, and calendar into one easy-to-use app so you can increase your performance. Instead of having to switch between different apps to jot down important information, create to-do lists, and glance at your calendar, Routine marries them all into one cool productivity tool. By simply using a keyboard shortcut, you can do all these things.
If you receive an email that contains an actionable item, you can convert that email into a task you can view later. Tasks are all saved in your inbox, and you can even schedule a task for a specific day. So, if Obi-Wan wants to have Jedi lessons on Thursday, you can schedule your Force task for that day. Likewise, chat messages that need follow-up can also be converted into tasks and be scheduled.
To enrich your tasks, notes can be attached to them. In your notes, you can also embed checkboxes, which are tasks of their own. And if you have tasks that aren’t coming from your inbox, you can import them from other services, such as Gmail, Notion, and Trello.
To make sure you can stay focused on the events and tasks at hand, Routine makes it easy to take everything in. By using the tool’s keyboard-controlled console, you can access your dashboard to quickly see what tasks need to be addressed, what’s on your calendar, and even join an upcoming Zoom session and take notes about the meeting.
Routine is available for macOS, iOS, web, and Google accounts only. Overall, the app centralizes notes and tasks by letting you create and view everything in one place, which helps make sure you stay on top of things. Currently, Routine is still in beta, but you can get on a waitlist to test the product out for yourself.
The paradox of CAPTCHAs: Too smart for humans vs AI?
(TECH NEWS) AI is catching up to our cybersecurity technology and often tricking humans too — so what’s next for CAPTCHAs and the internet?
We’ve all encountered it before: The occasional robot test that feels impossible to beat. If you’ve felt like these tests, also known as CAPTCHAs, have gotten harder in the last couple of years, you aren’t wrong—and the reason is as ironic as it is baffling.
Simply put, AI are just as good as—and often better than—humans at completing CAPTCHAs in their classic format. As machine learning and AI become more advanced, the fundamental human attributes that make consistent CAPTCHA formats possible become less impactful, raising the question of how to determine the difference between AI and humans in the future.
The biggest barrier to universal CAPTCHA doctrine is purely cultural. Humans may share experiences across the board, but such experiences are typically basic enough to fall victim to the same machine learning which has rendered lower-level CAPTCHAs moot. Adding a cultural component to CAPTCHAs could prevent AI from bypassing them, but it also might prevent some humans from understanding the objective.
Therein lies the root of the CAPTCHA paradox. Humans are far more diverse than any one test can possibly account for, and what they do have in common is also shared by—you guessed it—AI. To create a truly AI-proof test would be to alienate a notable portion of human users by virtue of lived experience. The irony is palpable, but one can only imagine the sheer frustration developers are going through in attempting to address this problem.
But all isn’t lost. While litmus tests such as determining the number of traffic cones in a plaza or checking off squares with bicycles (but not unicycles, you fool) may be beatable by machines, some experts posit that “human entropy” is almost impossible to mimic—and, thus, a viable solution to the CAPTCHA paradox.
“A real human being doesn’t have very good control over their own motor functions, and so they can’t move the mouse the same way more than once over multiple interactions,” says Shuman Ghosemajumder, a former click fraud expert from Google. While AI could attempt to feign this same level of “entropy”, the odds of a successful attempt appear low.
Move over, Clubhouse: Slack adds their own audio chat rooms
(TECH NEWS) Slack planning to co-opt Clubhouse’s synchronous audio rooms has lead to mixed response. Did it really need to be done?
Slack is adding a synchronous audio chat room feature similar to what Clubhouse already has. While not everyone is happy about it, the addition is true to Slack’s ongoing form—if a little redundant.
Slack’s audio rooms would work similarly to Clubhouse’s current feature of the same persuasion. The rooms themselves would be ongoing for as long as they were open, and users would be able to drop in and out of calls at their leisure, even joining the conversation when permitted by the host or settings. In theory, it’s a cool way to round out Slack’s platform and make for yet another way for people to engage during the work day.
But not everyone is stoked about the addition. Pocketnow’s Nadeem Sarwar makes a strong point about the redundancy of adding a Clubhouse feature to the already-packed Slack deck: “…from a regular remote worker’s perspective, I’d rather use services such as Telegram, Discord, or Google Meet that we’ve grown accustomed to using for jumping into a group call with my teammates.”
“…[T]he need for audio chatrooms to get in a chaotic chat with colleagues, with whom you already chat over work and share memes five days a week, doesn’t make much sense,” he adds.
Sarwar also references research about remote meeting fatigue from Stanford and The Washington Post, positing that—since video conferences are already played out at this point—adding another quasi-conference option to Slack doesn’t serve much of a purpose.
He isn’t wrong. There are multitudinous conference options on the market now, many of which are free. One could argue that Slack, having marketed itself as a text-first communication hub, has no business entering the audio chat landscape.
That argument falls on its face when you consider Slack’s model—something both Sawar and the Slack CEO himself mention—involves “stealing” and implementing “good ideas” from others in order to make their own platform as comprehensive as possible. If one is able to use Slack for the majority of tasks that Google, Discord, and Clubhouse offer, that makes the platform a lot more attractive to users who are on the fence.
And, perhaps more importantly, it ensures that current users won’t migrate to a comparable platform in the future—especially if their colleagues are making the same choice.
It’s a smart move for Slack, especially given Clubhouse’s lack of Android support at this time—something Clubhouse has said probably still won’t launch for a couple of months.
The Clubhouse team, for their part, continues to add new features in efforts to maintain the platform’s upward mobility. One such feature is the option for paid subscriptions to content creators, allowing for people to monetize their presence on the platform. At the time of this writing, Clubhouse is valued at around $1 billion.
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