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Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 11:55am

Avoiding IP issues when using generative AI

There are practical steps you can take right now to help ensure you're considered the creator, author, or inventor of something made with the assistance of generative AI.

Most importantly, be careful to document how and when you interact with AI tools, and what data you use for to gain an output. For the current generation of AI tools, this means you should record the prompts you use, when they were made, and with what version of tool. This could be crucial evidence down the track to show sufficient 'intellectual effort' was used, proving you're the rightful author or inventor.

If you're creating new AI tools, you should verify that you have sufficient rights in the datasets used to train the tools. This ensures the AI model that forms the basis of your tool can't inadvertently create a copy or a derivative work that would infringe on others' rights. It's likely more jurisdictions will require disclosure about training datasets as time goes on.

And finally, when using an AI tool, it's important to remember that you're accepting a license. That license affects your rights in the works, ideas or data output by the AI. Always read the fine print.

Despite the uncertainty and potential for massive changes, you can still get creating, inventing, and authoring—but know how to protect yourself, and do it responsibly.

 Source:  CSIRO 

Part 3

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If ChatGPT wrote it, who owns the copyright? It depends on where yo...

Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 11:54am

Humans vs. AI in Intellectual Property law

Many jurisdictions have decided only "real humans" can be considered the author, creator, or inventor for the purposes of IP law. But often it's unclear who is considered the creator of a work when an AI tool is used.

In the current generation of high-profile generative AI tools, text prompts are used as the input mechanism to produce a desired output. The question is, by entering a specific set of prompts into an AI tool, did a human apply sufficient effort to be considered the author, inventor or creator of the output work? If not, and the work is not considered a copy of any other work, then from where did the ingenuity or inventive effort come?

This line of thinking leads to several problems for people using and creating these tools, especially when it comes to proving they are the creator. More broadly, it poses problems for the entire IP system.

Let's hone in on the patent system as an example. One requirement for patenting is that a new invention must be "inventive," "not-obvious," contain an "inventive step," or other similar requirements across jurisdictions. The test for meeting this threshold is often defined as whether a person skilled in an area of technology, with access to their normal working tools, would consider the invention "routine," as "a matter of course," or "obvious."

If generative AI is used as a matter of course in an area of technology, and can produce an acceptable description of an invention, then the bar for patenting is significantly raised. That is, once generative AI tools become common place (maybe they already are), we can expect a person skilled in a particular area of technology will use them to solve their problems.

But what happens when an AI tool has become so proficient that it has collected every piece of data that a human could, and has awareness of every experience that a human could have? The AI would be able to conceive a solution to every problem that a human could, just as the chess computer knows every move a grandmaster may consider. The result is almost nothing is inventive anymore, unless the human inventor has new data they can input to which no other party (including the AI tool) has access.

This scenario helps to illustrate the issues that IP law and individuals face. It is likely that over the coming years step changes in technology will be taken that lawmakers will need to respond to. But, we don't yet know how these problems will be resolved. Given that no significant legal changes have been made in the face of the current generation of AI, and the rate of change is likely to accelerate, inventors and innovators should attempt to stay ahead of any possible changes.

Part 2

Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 11:53am

Changing face of invention in the age of AI

With the widespread adoption of generative AI tools like ChatGPT, we can no longer assume that new ideas and inventions are solely the result of human effort. So, what does this mean for inventors and the IP they create?

We've heard many perspectives recently on the effect generative AI will have on all facets of how we work, conduct business, and ultimately live our lives. When game-changing technologies emerge, there's a tendency for people to polarize in opinion, either vastly underestimating or vastly overestimating the benefits and problems associated with using them. For example, we've heard how AI could never produce art or how it will solve all our collective problems.

But no matter what our opinions are on the dangers and benefits of AI, these tools don't exist in isolation. People using and creating generative AI tools and the tools themselves are subject to IP laws. Being aware of these laws can help protect us from their impact.

When the tools we create become the creators

From the perspective of an artist, creator or author, there's a strong argument they should have a right to control how their work is used or exploited. Copyright laws generally achieve this goal. Typically, these laws rely on the legal concept of "individual intellectual effort" to determine who the author of a work is. That is, the person creating the work needs to have added enough of their own ingenuity and creativity to distinguish their creation from other existing works. But how does a human achieve this? Some argue that unlike AI, there's something special about humans that allows us to achieve the creation of a "new" work.

I propose a different argument. The work a human creates is simply the sum total of all the things that human has sensed and experienced throughout their lifetime. Similarly, an AI tool creates an output based on the sum total of all the data it has consumed throughout its training. With time, the data that an AI consumes will grow as its sensor inputs and ability to experience become more sophisticated. There's a critical point where AI tools will exceed humans in their ability to sense and experience, and consequently exceed humans in their capability to create, author or invent. At the very least, this will happen in specific domains. For example, AI's in the specific domain of chess exceeded human capability years ago, and we're witnessing it again now in the visual arts thanks to tools like Dall-E and Midjourney.

Part 1

Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 11:25am

In order to change the magnetism in the material investigated "by pushing a button," the researchers put the crystal under pressure. Starting from a kagome structure, the crystal lattice was deformed by uniaxial stress, which changed the magnetic interactions between the electrons.

Researchers used mechanical pressure to force the system into a preferred magnetic direction. The team succeeded in increasing the temperature of the magnetic phase transition by more than 10%

Jierong Wang et al, Controlled Frustration Release on the Kagome Lattice by Uniaxial-Strain Tuning, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.131.256501. On arXiv: DOI: 10.48550/arxiv.2209.08613

Part 2

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Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 11:23am

Researchers demonstrate how magnetism can be actively changed by pressure

Magnetism occurs depending on how electrons behave. For example, the elementary particles can generate an electric current with their charge and thereby induce a magnetic field. However, magnetism can also arise through the collective alignment of the magnetic moments (spins) in a material. What has not been possible until now, however, is to continuously change the type of magnetism in a crystal.

An international research team has now succeeded in doing just that: Changing magnetism  "by pushing a button." For that, the team continuously changed the magnetic interactions in a single crystal by applying pressure. The researchers recently published their results in Physical Review Letters.

Spins can be visualized as small compass needles that can align themselves in an external magnetic field and have a magnetic field themselves. In case of ferromagnetism, which is used in permanent magnets, all electron spins align parallel to each other. In some arrangements of electron spins, for example in ordinary square, checkerboard-type crystal lattices, an anti-parallel alignment of the spins is also possible: Neighboring spins always point alternately in opposite directions.

With triangular lattices (or lattices in which triangular structures occur, such as the more complex kagome lattice), a completely antiparallel arrangement is not possible: If two corners of a triangle have opposite spin directions, the remaining side must match one of the two directions. Both options—spin up or spin down—are then exactly equivalent. "This possibility of multiple identical alternatives is known as 'geometrical frustration' and occurs in crystal structures with electron spins arranged in triangular, kagome or honeycomb lattices.

The remaining unpaired magnetic moments could be entangled with each other, manipulated with external magnetic fields and thus used for data storage or computational operations in quantum computers.

In real materials, we are still far from such a state of ideal frustration. First of all, we need to be able to precisely control the symmetry of the crystal lattice and thus the magnetic properties

Part 1

Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 11:17am

Study details how biomimetic nanomaterials can minimize damage after a heart attack

A recent study details how, when targeted specifically to the spleen, histone deacetylase (HDAC) inhibitors, chemical compounds that can be used to treat cancers and other diseases, can potentially improve the healing response following a heart attack.

Normally, immune cells  migrate from the spleen to the heart after a heart attack in response to injury. Here, researchers found that they could design nanomaterials that mimic dead and dying red blood cells, causing them to be retained in the spleen and enabling them to deliver inhibitors that modulate the inflammatory response.

Notably, this targeting strategy significantly decreases cardiac scar size and the preservation of heart function, even after just one dose, when given within two hours of heart attack injury.

 Rajendran JC Bose et al, Biomimetic Nanomaterials for the Immunomodulation of the Cardiosplenic Axis Postmyocardial Infarction, Advanced Materials (2023). DOI: 10.1002/adma.202304615

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Mineral coatings could enable shelf-stable mRNA therapies

A protective mineral coating identified by University of Wisconsin–Madison biomedical engineering researchers could allow powerful messenger RNA therapeutics like COVID-19 vaccines to be stored at room temperature, making them more accessible to lower-resourced communities across the world.

Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 11:13am

Why paint does not dry slower in a humid environment

A team of physicists  working with an infection and immunity specialist  has, via experimentation, validated a theory to explain why paint dries at the same rate regardless of humidity levels. The study is published in Physical Review Letters.

Common sense suggests that paint should dry faster on an outdoor fence on a dry day than when it is humid because evaporation occurs faster when the air around a liquid source is drier. But anecdotal evidence suggests this is not the case for paint and other liquids. Six years ago, chemists developed a theory to explain why this is the case. They suggested it is because large molecules in the liquid are pulled to the surface during evaporation, forming a 'polarization layer' that inhibits evaporation, and by extension, drying. In this new effort, the research team conducted an experiment to test this theory.

The researchers found that in their experiments evaporation rates remained constant for approximately three hours. But then, rates plummeted, as was theorized by chemists, regardless of humidity levels. The evaporation rate did not decrease as humidity increased during the initial three hours. However, the theory only appeared to hold for humidity levels up to 80%—at rates higher than that, evaporation did slow down, which the team suggests was likely due to some other force.

The researchers suggest their work could have medical applications as recent research efforts have shown that respiratory droplets tend to form skins similar to those seen in the experimental apparatus.

Max Huisman et al, Evaporation of Concentrated Polymer Solutions Is Insensitive to Relative Humidity, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.131.248102

Comment by Dr. Krishna Kumari Challa on December 21, 2023 at 9:54am

Using AI, researchers identify a new class of antibiotic candidates that can kill a drug-resistant bacterium

Using a type of artificial intelligence known as deep learning, researchers have discovered a class of compounds that can kill a drug-resistant bacterium that causes thousands of deaths around the world every year.

In a  study  appearing in Nature, the researchers showed that these compounds could kill methicillin-resistant Staphylococcus aureus (MRSA) grown in a lab dish and in two mouse models of MRSA infection. The compounds also show very low toxicity against human cells, making them particularly good drug candidates. A key innovation of the new study is that the researchers were also able to figure out what kinds of information the deep-learning model was using to make its antibiotic potency predictions. This knowledge could help researchers to design additional drugs that might work even better than the ones identified by the model.

James Collins, Discovery of a structural class of antibiotics with explainable deep learning, Nature (2023). DOI: 10.1038/s41586-023-06887-8. www.nature.com/articles/s41586-023-06887-8

Comment by Dr. Krishna Kumari Challa on December 20, 2023 at 10:53am

Flu has long-term illness risk — like COVID

People who have been very ill with flu could develop a long-haul illness similar to long COVID. The medical records of more than 81,000 people who were hospitalized with COVID-19 and almost 11,000 with flu show that both infections carried a risk of health problems in the following .... ‘Long flu’ symptoms were more likely to be respiratory — shortness of breath or cough. We need to “stop trivialising viral infections and understand that they are major drivers of chronic diseases”, says clinical epidemiologist and study co-author Ziyad Al-Aly.

Reference: The Lancet Infectious Diseases paper

Comment by Dr. Krishna Kumari Challa on December 20, 2023 at 10:50am

What we can expect in the year 2024 in the field of science

The consciousness debate: round two

Next year could bring new insights into the neural basis of consciousness. A large project that is testing two theories of consciousness through a series of adversarial experiments is expected to release the results of its second experiment by the end of 2024. In the first round, both theories failed to completely align with observed brain-imaging data, settling a 25-year bet in favour of philosophy over neuroscience. The second round could put neuroscience closer to deciphering the mysteries of the subjective experience.

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Saving the planet

In the second half of 2024, the International Court of Justice in the Hague could give an opinion on nations’ legal obligations to combat climate change, and rule on legal consequences for those deemed to be damaging the climate. Although the ruling will not be legally binding, the court’s clout can push countries to strengthen their climate goals and can be cited in domestic legal cases.

Negotiations for the UN plastics treaty, which seeks to establish a binding international agreement to eliminate plastic pollution, will wrap up next year. Since the 1950s, the world has produced 10 billion tonnes of plastic, of which more than 7 billion tonnes is now waste — much of which is polluting oceans and harming wildlife. But there is growing concern among researchers that the UN negotiations, which started last year, are advancing too slowly and will not accomplish the intended goals.

https://www.nature.com/articles/d41586-023-04044-9?utm_source=Live+...

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