Disruptive science in decline

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Published on: January 6, 2023

An interesting article and study about decline in disruptive science in most research fields.

Few excerpts from the article:

Disruptiveness is not inherently good, and incremental science is not necessarily bad, says Wang.”

Finding an explanation for the decline won’t be easy, Walsh says. Although the proportion of disruptive research dropped significantly between 1945 and 2010, the number of highly disruptive studies has remained about the same. The rate of decline is also puzzling: CD indices fell steeply from 1945 to 1970, then more gradually from the late 1990s to 2010. “Whatever explanation you have for disruptiveness dropping off, you need to also make sense of it levelling off” in the 2000s, he says.

More of this here @nature: [The link]

DISRUPTIVE SCIENCE DWINDLES. Chart shows disruptiveness of papers has fallen over time in all analysed fields.

Nuclear Fusion: Seems there is a major (scientific) breakthrough

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Published on: December 16, 2022

Lots of articles and hype around Nuclear Fusion these days (dec 2022). Seems this time around it is a breakthrough of some scientific significance. A nice article from MITTech review explaining and putting results in context of current progress.

e.g. “..This is a big moment for fusion power, a basic test that the field has been striving for since researchers started dreaming about it in the 1950s. That deserves to be celebrated, and I think it’s fine to get excited about it. It’s a true milestone.

But…we need to be clear here. This is primarily a scientific achievement. Fusion has a long way to go to be a technology that we’re really using in our daily lives.”

More of this here: [The Link]

Generative AI: is this something new?

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Published on: October 29, 2022

A nice summary of the recent trends in AI, where we get these cool new images or art generated by AI. See more of this in the article from Techcrunch: [The Link]

 

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TC: There’s a lot of confusion about generative AI, including how new exactly it is, or whether it’s just become the latest buzzword.

JC: I think what happened to the AI world in general is that we had a sense that we could have deterministic AI, which would help us identify the truth of something. For example, is that a broken piece on the manufacturing line? Is that an appropriate meeting to have? It’s where you’re determining something using AI in the same way that a human determines something. That’s largely what AI has been for the last 10 to 15 years.

The other sets of algorithms in AI were more these diffusion algorithms, which were intended to look at huge corpuses of content and then generate something new from them, saying, ‘Here are 10,000 examples. Can we create the 10,001st example that is similar?’

Those were pretty fragile, pretty brittle, up until about a year and a half ago. [Now] the algorithms have gotten better. But more importantly, the corpuses of content we’ve been looking at have gotten bigger because we just have more processing power. So what’s happened is, these algorithms are riding Moore’s law — [with vastly improved] storage, bandwidth, speed of computation — and have suddenly become able to produce something that looks very much like what a human would produce. That means the face value of the text that it will write, and the face value of the drawing it will draw, looks very similar to what a human will do. And that’s all taken place in the last two years. So it’s not a new idea, but it’s newly at that threshold. That’s why everyone looks at this and says, ‘Wow, that’s magic.’

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[2022] Status of AI based image generation

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Published on: August 3, 2022

Interesting article on the status of automated generation of images using AI. Some snippets from the article

“..Lots of labs and companies are working on similar technologies that turn text into imagery. Google has Imagen, OpenAI has DALL-E, and there are a handful of smaller projects like Craiyon. “

“..AI-generated artwork is quietly beginning to reshape culture. Over the last few years, the ability of machine learning systems to generate imagery from text prompts has increased dramatically in quality, accuracy, and expression. Now, these tools are moving out of research labs and into the hands of everyday users, where they’re creating new visual languages of expression and — most likely — new types of trouble.”

 

More of this here from Verge: [The Link]

[Harpers]: Routine maintenance: embracing habit in modern world

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Published on: January 14, 2022

Habit & Routine can be very helpful in some aspects but also can be crippling in other aspects. Came across this very interesting & thoughtful article about habits, its history, its relevance in social lifes from past and present, but also some thoughts on role of automation in society.

An interesting passage towards the end for balance & reflection:

“…But even the most ingrained human behaviors are accompanied by sensations that prompt us to pause and recalibrate when something goes wrong—a truth well known to anyone who has caught themselves driving home to a previous residence or gagging on the hemorrhoid cream they’ve mistaken for toothpaste. Ravaisson calls habit the “moving middle term,” a disposition that slides along the continuum between rote mechanism and reflective freedom. Weil, who similarly saw habit as a continuum, believed that we should strive to remain on the reflective side of that spectrum. The Stoics advised nightly meditation, so as to judge the virtue of the actions they’d taken that day, and Charles Sanders Peirce, the father of pragmatism, noted that in cases where habits have begun to work against a person’s interests, “reflection upon the state of the case will overcome these habits, and he ought to allow reflection its full weight.” It is this connection to thought that allows habits to remain fluid and flexible in a way that machines are not. Habits are bound up with the brain’s plasticity, a term James describes as “a structure weak enough to yield to an influence, but strong enough not to yield all at once.” Unlike algorithms, which lock in patterns and remain beyond our understanding, habits allow us to negotiate a livable equilibrium between thought and action, maintaining, as Weil puts it, “a certain balance between the mind and the object to which it is being applied.” .. ”

 

More about this article here: [The Link]

Fact vs. fake – why don’t we trust science any more? | DW Documentary

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Published on: May 8, 2021

A pretty interesting documentary from DW on this topic.

 
Also, learned about this intereresting field of Agnotology: A study of culturally induced ignorance or doubt, particularly the publication of inaccurate or misleading scientific data. Wiki Link

Top 10 emerging tech from 2020 [SciAmerican]

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Published on: April 4, 2021

Below is a list of top 10 emerging tech in 2020 as identified by Scientific American.

More of these technologies at SciAm here: [The Link]

  • Microneedles could enable painless injections and blood draws
  • Sun-powered chemistry can turn carbon dioxide into common materials
  • Virtual patients could revolutionize medicine
  • Spatial computing could be the next big thing
  • Digital medicine can diagnose and tread what ails you
  • Electric aviation could be closer than you think
  • Low-carbon cement can help combat climate change
  • Quantum sensors could let autonomous cars see around corners
  • Green hydrogen could fill big gaps in renewable energy
  • whole-genome synthesis will transform cell engineering

[NYtimes] A collection long-form articles in 2020

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Published on: February 7, 2021

Recently came across a great collection of articles from David Brooks in the NYtimes. It has been Brook’s recurring list as Sydney Awards. Here is the list and brief commentary on each from David Brooks [NYTimes article Link] Here are the articles mentioned the above link:

Few on the lighter side of things, also from the same NYTimes article:

 

A 25-Year-Old Bet Comes Due: Has Tech Destroyed Society?

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Published on: January 30, 2021

Recently read about this long term bet between K. Kelly (techno optimist) and K. Sale (techno skeptic). The best was set in 1995 that by 2020 the world would collapse and tech aspects would have been a major contributing factor in driving the collapse (economic, climate & inequality). Few interesting excerpts from the article here, especially by the arbiter W. Patrick:

 

Economic Collapse. Sale predicted flatly that the dollar and other accepted currencies would be worthless in 2020. Patrick points to the Dow at 30,000 and the success of new currencies such as Bitcoin. “Not much contest here,” Patrick writes. Round goes to Kelly.

Global Environmental Disaster. Kelly tried to argue that despite worsening climate change, people are still living their lives pretty much as usual. “If this is a disaster, that is not evident to Earth’s 7 billion inhabitants,” Kelly wrote in his four-page argument. But Patrick isn’t convinced. “With fires, floods, and rising seas displacing populations; bugs and diseases heading north; ice caps melting and polar bears with no place to go; as well as the worst hurricane season and the warmest year on record, it’s hard to dispute that we are at least ‘close to’ global environmental disaster,” Patrick wrote in his final decision. This one is Sale’s.

The War Between Rich and Poor. Sale’s book cites devastating statistics on income inequality and the frayed social fabric. If he had written his book after the pandemic, the picture would be even worse. But are the classes at war? Patrick notes that in the decades since Kelly and Sale made the bet, breathtaking economic development has reshaped China and India, among other countries. On the other hand, he points to undeniable social unrest, even in the United States, with Trumpites taking to the streets with semiautomatic weapons, and massive protests against police abuses. He calls this round a toss-up, with an edge to Sale.

 

Of course, all bets are off. They have not yet resolved the bet.

Read more of this here from WIRED: [The Link]

Genetic editing key design space

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Published on: January 4, 2021

Genetic editing is a very broad term used for techniques used in various different domains. With recent Crispr tech, this technology, especially in human context is currently in debate/discussion in all forums. One categorization that gives some clarity in this discussion is from a short documentary in Netflix Explained: Designer DNA. This figure explains the design space of editing DNA.

Somatic: DNA does not get passed down to off spring

Germline: DNA passes to next generation

More of this here:  Explained: episode on Designer DNA

Article explaining this in more detail: [Article in Medium]

A mini series in Netflix: Unnatural Selection

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