"I have no special talents. I am only passionately curious."
― Albert Einstein
I feel just the same without the distinction of the great scientist. I regularly read articles and book reviews from Nature to keep abreast of latest developments in science and technology. I love science and my second love is economics. If only can roll back time machine would study both. As Cohen sang " ― "Then let me start again," I cried, "please let me start again, I want a face that's fair this time, I want a spirit that is calm." It is this complex that drives me to read and study. Its like a paltry tribute to one's persistent longing. The spirit is calm now and face is....
Einstein after studying in ETH university in Zurich worked at the patent office in Bern where he did much of his pioneering works in Physics which lead to Nobel Prize in Physics in 1921. Einstein won Nobel prize " for his services to Theoretical Physics, and especially for his discovery of the law of the photoelectric effect." I guess it doesn't matter where you work and what and how you work is most important. So many people judge you either by your grades or your organization. Grades is meritocracy and organization is relationship skills. How ever the consequence of work should be consequential and that is what matters when it comes to scientific break through's like mRNA vaccines which really saved millions of lives during pandemic . Infectious disease Epidemiologist & WHO expert Maria Van Kherkhove posted on X platform "Sadly at the end of 2023, we passed the 7 million mark for the number of #COVID19 deaths reported to @WHO . 7,010,586 to be exact. The true death toll is higher, with estimates of at >3 times more deaths globally." ( Jan 11, 2024) If we take the excess death toll into account its around 20+ million. That's lot of people and considering this the vaccines could have saved equal number of people - 20 + million or more. Am doing a guesstimate. That's what a breakthrough technology can do. It saves lives.
According to Nature report seven technologies to watch in 2024:
- Deep learning for protein design
- Deepfake detection
- Large -fragment DNA insertion
- Brain -computer interfaces
- Super -duper resolution
- Cell atlases
- Nano materials printed in 3D
Let's explore one or two of above from the nature article
Deep learning for protein design
"Two decades ago, David Baker at the University of Washington in Seattle and his colleagues achieved a landmark feat: they used computational tools to design an entirely new protein from scratch. 'Top7' folded as predicted, but it was inert: it performed no meaningful biological functions. Today, de novo protein design has matured into a practical tool for generating made-to-order enzymes and other proteins. "It's hugely empowering," says Neil King, a biochemist at the University of Washington who collaborates with Baker's team to design protein-based vaccines and vehicles for drug delivery. "Things that were impossible a year and a half ago — now you just do it."
Much of that progress comes down to increasingly massive data sets that link protein sequence to structure. But sophisticated methods of deep learning, a form of artificial intelligence (AI), have also been essential.
'Sequence based' strategies use the large language models (LLMs) that power tools such as the chatbot ChatGPT (see 'ChatGPT? Maybe next year'). By treating protein sequences like documents comprising polypeptide 'words', these algorithms can discern the patterns that underlie the architectural playbook of real-world proteins. "They really learn the hidden grammar," says Noelia Ferruz, a protein biochemist at the Molecular Biology Institute of Barcelona, Spain. In 2022, her team developed an algorithm called ProtGPT2 that consistently comes up with synthetic proteins that fold stably when produced in the laboratory1. Another tool co-developed by Ferruz, called ZymCTRL, draws on sequence and functional data to design members of naturally occurring enzyme families2.
Sequence-based approaches can build on and adapt existing protein features to form new frameworks, but they're less effective for the bespoke design of structural elements or features, such as the ability to bind specific targets in a predictable fashion. 'Structure based' approaches are better for this, and 2023 saw notable progress in this type of protein-design algorithm, too. Some of the most sophisticated of these use 'diffusion' models, which also underlie image-generating tools such as DALL-E. These algorithms are initially trained to remove computer-generated noise from large numbers of real structures; by learning to discriminate realistic structural elements from noise, they gain the ability to form biologically plausible, user-defined structures.
RFdiffusion software3 developed by Baker's lab and the Chroma tool by Generate Biomedicines in Somerville, Massachusetts4, exploit this strategy to remarkable effect. For example, Baker's team is using RFdiffusion to engineer novel proteins that can form snug interfaces with targets of interest, yielding designs that "just conform perfectly to the surface," Baker says. A newer 'all atom' iteration of RFdiffusion5 allows designers to computationally shape proteins around non-protein targets such as DNA, small molecules and even metal ions. The resulting versatility opens new horizons for engineered enzymes, transcriptional regulators, functional biomaterials and more."
Deepfake detection
"The explosion of publicly available generative AI algorithms has made it simple to synthesize convincing, but entirely artificial images, audio and video. The results can offer amusing distractions, but with multiple ongoing geopolitical conflicts and a US presidential election on the horizon, opportunities for weaponized media manipulation are rife.
Siwei Lyu, a computer scientist at the University at Buffalo in New York, says he's seen numerous AI-generated 'deepfake' images and audio related to the Israel–Hamas conflict, for instance. This is just the latest round in a high-stakes game of cat-and-mouse in which AI users produce deceptive content and Lyu and other media-forensics specialists work to detect and intercept it.
One solution is for generative-AI developers to embed hidden signals in the models' output, producing watermarks of AI-generated content. Other strategies focus on the content itself. Some manipulated videos, for instance, replace the facial features of one public figure with those of another, and new algorithms can recognize artefacts at the boundaries of the substituted features, says Lyu. The distinctive folds of a person's outer ear can also reveal mismatches between a face and a head, whereas irregularities in the teeth can reveal edited lip-sync videos in which a person's mouth was digitally manipulated to say something that the subject didn't say. AI-generated photos also present a thorny challenge — and a moving target. In 2019, Luisa Verdoliva, a media-forensics specialist at University Federico II of Naples, Italy, helped to develop FaceForensics++, a tool for spotting faces manipulated by several widely used software packages6. But image-forensic methods are subject- and software-specific, and generalization is a challenge. "You cannot have one single universal detector — it's very difficult," she says.
And then there's the challenge of implementation. The US Defense Advanced Research Projects Agency's Semantic Forensics (SemaFor) programme has developed a useful toolbox for deepfake analysis, but, as reported in Nature (see Nature 621, 676–679; 2023) major social-media sites are not routinely employing it. Broadening the access to such tools could help to fuel uptake, and to this end Lyu's team has developed the DeepFake-O-Meter7, a centralized public repository of algorithms that can analyse video content from different angles to sniff out deepfake content. Such resources will be helpful, but it is likely that the battle against AI-generated misinformation will persist for years to come."
― Seven technologies to watch in 2024, Michael Einsenstein, 22 Jan 2024, Nature
More: https://www.nature.com/articles/d41586-024-00173-x?utm_source=Live+Audience&utm_campaign=17a8b67978-briefing-dy-20240122&utm_medium=email&utm_term=0_b27a691814-17a8b67978-51036312
According to a news report:
India, along with Bangladesh and Pakistan, is among the top ten countries in Asia-Pacific most affected by identity fraud that is committed using deepfake technology, according to a leading digital identity verification firm. The UK-based Sumsub Identity Fraud Report says 2023 recorded a significant rise in such cybercrimes, which will increase further next year.
Vietnam leads the region with 25.3 per cent of the total deepfake identity frauds, followed by Japan at 23.4 per cent, Australia at 9.2 per cent, China at 7.7 per cent, and Bangladesh at 5.1 per cent, according to the data derived from an analysis of over two million fraud attempts in 224 countries and territories across 28 industries.
― India among top targets of deepfake identity frauds, Subham Tiwari, India Today. Dec 5, 2023
More:https://www.indiatoday.in/india/story/india-among-top-targets-of-deepfake-identity-fraud-2472241-2023-12-05
With 2024 elections round the corner in many countries deepfake detection needs to be vigil;ant and countries need expertise to counter media manipulation and smear campaigns.
Google Deepmind's Alpha Fold solution to solve the protein folding problem
AlphaFold was taught by showing the sequences and structures of around 100,000 known proteins.
It can now predict the shape of a protein, almost instantly, down to atomic accuracy.
AlphaFold was recognised as a solution to the grand challenge of protein-folding by CASP (Critical Assessment of protein Structure Prediction), a community for researchers to share progress on their predictions against real experimental data.
―AlphaFold, https://deepmind.google/technologies/alphafold/
Advances in AI and deep learning is fueling much of these technologies. I hope to follow more on these seven technologies . Elon Musk posted on X " The first human received an implant from @Neuralink yesterday and is recovering well. Initial results show promising neuron spike detection." I think Brain - computer interfaces advances are very encouraging.
Today is Mahatma Gamdhi Martyrs' Day ( Shaheed Diwas) and wonder what would Gandhiji say on advances in AI , perhaps " You must not lose faith in humanity. Humanity is an ocean; if few drops of ocean are dirty, the ocean does not become dirty." ( Mahatma Gandhi)
Today is also my brother's birthday!
Sincerely, Suresh
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