Suramya's Blog : Welcome to my crazy life…

April 19, 2023

Finally a useful AI Implementation: Making spoken dialog easier to hear in movies and shows

Filed under: Emerging Tech,News/Articles,Tech Related — Suramya @ 6:37 PM

Finally, an AI usecase that is actually useful. There are a ton of use cases where AI seems to be shoehorned in for no reason, but this recent announcement from Amazon about Dialogue Boost which is a new function from that lets you increase the volume of dialogue relative to background music and effects to a consistent volume so you can actually hear the dialog without nearly shattering the eardrums when a sudden explosion happens.
It is something that is still in the testing phase and is only released on some of their products so far. But I am looking forward to it being in general availability.

Dialogue Boost works by analyzing the original audio in a movie or series and identifying points where dialogue may be hard to hear above background music and effects, at which point speech patterns are isolated and audio is enhanced to make the dialogue clearer. The AI targets spoken dialogue rather than a typical speaker or home theater set up that only amplifies the center channel of audio. It’s something that exists on high-end theater set-ups and certain smart TVs, but Amazon is the first streamer to roll out such a feature.

I have gotten used to having subtitles on when I watch something because that ensures that I don’t miss out on any dialogs due to the background music/sounds in the show/movie. This looks like it will alleviate that requirement. I think I will still end up keeping the subtitles on but this will certainly help.

Source: Amazon’s New Tool Adjusts Sound So You Can Actually Understand Movie and TV Dialogue
Announcement: Prime Video launches a new accessibility feature that makes it easier to hear dialogue in your favorite movies and series

– Suramya

March 18, 2023

Scientists create a working supersolid in the lab

Filed under: Emerging Tech,My Thoughts — Suramya @ 11:34 PM

It seems that every year we learn more about the universe that makes the basic physics that we learned in school inaccurate or rather puts a lot of caveats in to the theories. Originally we had 3 states of matter: Solid, liquid and gas. Then came things like superfluids, Bose–Einstein condensates, quantum spin liquid, supercritical fluid, quark–gluon plasma, Rydberg polaron, and so many more weird possibilities. Last week, scientists from Innsbruck University in Austria have managed to create a new state of matter in 2D called Supersolids. Till now the researchers had only been able to create a 1D (a few molecules long) chain of SuperSolids but using cutting edge research they were able to create a 2D ‘paper’ of supersolid.

If you are like me, by now you will be wondering what on earth is a supersolid… Basically it is a state of matter that incorporates two different states of matter at the same time i.e. it is a solid as well as a superfluid at the same time. This gives it the ability to be a solid and still flow like a liquid without any friction at the same time. If that sounds confusing it is so because we are talking about Quantum effects which seem to exist in a state of constant contradiction and confusion (At least for me, when I try to understand them).

“To picture a supersolid, consider an ice cube immersed in liquid water, with frictionless flow of the water through the cube,” wrote Bruno Labruthe-Tolra, a physicist at Sorbonne Paris North University.

So, to create a supersolid, you first trap some atoms, then cool them, then play with their interactions. “If you tune those correctly, and you tune the shape of the trap correctly, you can get a supersolid,” says Norcia, the lead author.

Using this method, in 2019, researchers began to create a basic, one-dimensional supersolid: essentially, a thin supersolid tube in a straight line.

That’s what Norcia and his colleagues at Innsbruck University and the Austrian Academy of Sciences have now done. By tinkering with the device they used to trap atoms and the process they used to condense the atoms, they were able to extend their supersolid from one dimension into two: from a tiny tube into a small sheet.

There are a lot of interesting usecases for this technology when it matures, we could use it for lubrication in industrial machinery, create frictionless surfaces for tests. It could even be used in vacuum as is for various usecases. But that is still quite a way off because the work to go from 2D to 3D has just started and is still in the pre-research stage. However, while that is going on we do have a superSolid paper available for study while will give us more insight into this fascinating new substance.

The research has been published in Nature: Supersolids go two-dimensional

Source: Popsci.com: We finally have a working supersolid. Here’s why that matters.

– Suramya

March 12, 2023

Researchers create mini-robot that can navigate inside blood vessels and perform surgery autonomously

Filed under: Emerging Tech,Tech Related — Suramya @ 11:13 PM

Performing surgery is a delicate task and at times it is almost impossible to reach the area we want to operate at without having to cut through other important tissues. This is even more apparent when we talk about surgery inside a blood vessel or artery, which could be the key to removing an obstruction or stitch a wound etc. Till now we didn’t have the ability to release an autonomous robot inside a blood vessel that could navigate to the correct location, perform the programmed actions (or allow the doctor to manually take over) and return.

This was only possible in the realm of Science Fiction but thanks to the efforts of Researchers at South Korea’s Hanyang University this is now actually possible in the real world. They have successfully demonstrated that their I-RAMAN (robotically assisted magnetic navigation system for endovascular intervention) robot can travel autonomously to a superficial femoral artery in a pig, deliver contrast dye, and return safely to the extraction point. Their results and paper was published on 9th Feb in IEEE Robotics and Automation Letters: Separable and Recombinable Magnetic Robot for Robotic Endovascular Intervention.

This study presents a separable and recombinable magnetic robot (SRMR) to deliver and retrieve an untethered magnetic robot (UMR) to a target vascular lesion safely and effectively for robotic endovascular intervention. The SRMR comprises a delivery catheter and UMR connected to the end of the delivery catheter by a connecting section. An external magnetic field (EMF) interacts with the permanent magnet of the UMR; it can effectively generate magnetic torque and steer the delivery catheter to reach a target lesion. Furthermore, the rotating EMF allows the UMR of the SRMR to separate from the delivery catheter and perform the tunneling task. After completing the tunneling task, the UMR can be safely recombined with the delivery catheter in the vasculature via a simultaneous application of the EMF and suction force to the delivery catheter. The SRMR functions of steering, separation, movement, tunneling, drug delivery, and recombination are validated in a mimetic vascular model with a pseudo blood clot. Finally, the SRMR is successfully validated in an in vivo experiment of a mini pig’s superficial femoral artery for contrast delivery, separation, movement, and recombination.

This is a fantastic achievement, and although there is a lot of work still left to be done before this can be deployed for actual human use we are still a step closer to truly universal repair bots. Imagine an accident victim who is bleeding internally, the doctor deploys these robots to restitch the blood vessels to stop the internal bleeding and within minutes the bleeding is stopped and the doctor can start the post-op work. I can imagine these being sold as part of the standard medkits in the future (way in the future) where you have a few pre-programmed options available and depending on the situation a person can select the correct option to deploy.

However, all is not rosy (as always). If these go into active use and become common enough to be deployed in med-kits then we would need systems to prevent these bots from being repurposed. For example, instead of being programmed to stitch blood vessels the bots are programmed to cause more damage and start internal bleeding. There are so many other scenarios where this could be misused so we would need to think of all the cases, mitigate the risk and only then deploy them into the world.

That being said, I am still excited to see the possibilities this opens up.

Source: ACM Tech News Newsletter.

– Suramya

March 2, 2023

Intel Releases SDK allowing C++ Developers to start writing code for Quantum Computers

Filed under: Quantum Computing,Tech Related — Suramya @ 8:26 PM

Intel has released a new software platform for Developers (SDK) who are looking to work on Quantum computers. They are not the first (Microsoft released an online course/setup back in 2019) and they certainly won’t be the last to do this.

Unfortunately, while they have released the platform it doesn’t actually run on a quantum computer but rather runs on a quantum computer simulator they have built. But the really interesting thing is that this SDK that they have released allows developers to use C++ to build quantum algorithms instead of having to learn a new programming language which immediately increases the no of people who can hit the ground running and start developing with the SDK.

The platform, called Intel Quantum SDK, would for now allow those algorithms to run on a simulated quantum computing system, said Anne Matsuura, Intel Labs’ head of quantum applications and architecture. Matsuura said developers can use the long-established programming language C++ to build quantum algorithms, making it more accessible for people without quantum computing expertise. “The Intel Quantum SDK helps programmers get ready for future large-scale commercial quantum computers,” Matsuura said in a statement. “It will also advance the industry by creating a community of developers that will accelerate the development of applications.”

Intel will be launching their own version of a Quantum computer in the near future. They are taking a slightly different approach than the others to make the computer, they are basically trying to build this computers using their existing chip-making technology by putting transistors very close to each other, running them at super low temperatures and then use single electrons in the circuit which makes the transistors act as qubits. This sounds like a promising approach but I feel that this is more of a stepping stone on the way to the fully quantum setup as it is a hybrid version of the existing computers and a quantum computer.

Source: Slashdot: Intel Releases Software Platform for Quantum Computing Developers

– Suramya

February 27, 2023

It is now possible to put undetectable Backdoors in Machine Learning Models

Filed under: Computer Software,Emerging Tech,My Thoughts,Tech Related — Suramya @ 10:18 PM

Machine Learning (ML) has become the new go to buzzword in the Tech world in the last few years and everyone seems to be focusing on how they can include ML/AI in their products, regardless of whether it makes sense to include or not. One of the bigest dangers of this trend is that we are moving towards a future where an algorithm would have the power to make decisions that have real world impacts but due to the complexity it would be impossible to audit/check the system for errors/bugs, non-obvious biases or signs of manipulation etc. For example, we have had cases where the wrong person was identified as a fugitive and arrested because an AI/ML system claimed that they matched the suspect. Others have used ML to try to predict crimes with really low accuracy but people take it as gospel because the computer said so…

With ML models becoming more and more popular there is also more research on how these models are vulnerable to attacks. In December 2022 researchers (Shafi Goldwasser, Michael P. Kim, Vinod Vaikuntanathan and Or Zamir) from UC Berkely, MIT and Princeton published a paper titled “Planting Undetectable Backdoors in Machine Learning Models” in the IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS) where they discuss how it would be possible to train a model in a way that it allowed an attacker to manipulate the results without being detected by any computationally-bounded observer.

Abstract: Given the computational cost and technical expertise required to train machine learning models, users may delegate the task of learning to a service provider. Delegation of learning has clear benefits, and at the same time raises serious concerns of trust. This work studies possible abuses of power by untrusted learners.We show how a malicious learner can plant an undetectable backdoor into a classifier. On the surface, such a backdoored classifier behaves normally, but in reality, the learner maintains a mechanism for changing the classification of any input, with only a slight perturbation. Importantly, without the appropriate “backdoor key,” the mechanism is hidden and cannot be detected by any computationally-bounded observer. We demonstrate two frameworks for planting undetectable backdoors, with incomparable guarantees.

First, we show how to plant a backdoor in any model, using digital signature schemes. The construction guarantees that given query access to the original model and the backdoored version, it is computationally infeasible to find even a single input where they differ. This property implies that the backdoored model has generalization error comparable with the original model. Moreover, even if the distinguisher can request backdoored inputs of its choice, they cannot backdoor a new input­a property we call non-replicability.

Second, we demonstrate how to insert undetectable backdoors in models trained using the Random Fourier Features (RFF) learning paradigm (Rahimi, Recht; NeurIPS 2007). In this construction, undetectability holds against powerful white-box distinguishers: given a complete description of the network and the training data, no efficient distinguisher can guess whether the model is “clean” or contains a backdoor. The backdooring algorithm executes the RFF algorithm faithfully on the given training data, tampering only with its random coins. We prove this strong guarantee under the hardness of the Continuous Learning With Errors problem (Bruna, Regev, Song, Tang; STOC 2021). We show a similar white-box undetectable backdoor for random ReLU networks based on the hardness of Sparse PCA (Berthet, Rigollet; COLT 2013).

Our construction of undetectable backdoors also sheds light on the related issue of robustness to adversarial examples. In particular, by constructing undetectable backdoor for an “adversarially-robust” learning algorithm, we can produce a classifier that is indistinguishable from a robust classifier, but where every input has an adversarial example! In this way, the existence of undetectable backdoors represent a significant theoretical roadblock to certifying adversarial robustness.

Basically they are talking about having a ML model that works correctly most of the time but allows the attacker to manipulate the results if they want. One example use case would be something like the following: A bank uses a ML model to decide if they should give out a loan to an applicant and because they don’t want to be accused of being discriminatory they give it to folks to test and validate and the model comes back clean. However, unknown to the testers the model has been backdoored using the techniques in the paper above so the bank can modify the output in certain cases to deny the loan application even though they would have qualified. Since the model was tested and ‘proven’ to be without bias they are in the clear as the backdoor is pretty much undetectable.

Another possible attack vector is that a nation state funds a company that trains ML models and has them insert a covert backdoor in the model, then they have the ability to manipulate the output from the model without any trace. Imagine if this model was used to predict if the nation state was going to attack or not. Even if they were going to attack they could use the backdoor to fool the target into thinking that all was well.

Having a black box making such decisions is what I would call a “Bad Idea”. At least with the old (non-ML) algorithms we could audit the code to see if there were issues with ML that is not really possible and thus this becomes a bigger threat. There are a million other such scenarios that could be played and if we put blind trust in an AI/ML system then we are setting ourselves up for a disaster that we would never see coming.

Source: Schneier on Security: Putting Undetectable Backdoors in Machine Learning Models

– Suramya

February 1, 2023

Product Idea: Use ChatGPT to write movie/TV Tech Jargon dialogs

Filed under: Emerging Tech,My Thoughts,Tech Related — Suramya @ 3:00 AM

ChatGPT has taken the world by storm and everyday we hear more and more stories about how good it is and how it is changing the world. Personally I think the best description of the software is how Christine Lemmer-Webber put it:

ChatGPT is Mansplaining As A Service. A service that instantly generates vaguely plausible sounding yet totally fabricated and baseless lectures in an instant with unflagging confidence in its own correctness on any topic, without concern, regard or even awareness of the level of expertise of its audience.

People are using it for anything and everything including writing exams, writing articles, job posts, etc etc. While the result we get looks quite plausible there have been multiple cases where the output is subtly wrong and using the result as is can cause problems. However, there is one place that I can think of that ChatGPT would be extremely useful without any major drawbacks. If you have seen any TV show recently there are a lot of times where the characters will use technobabble to explain something and a lot of times the explanations are so ridiculous that they end up distracting you from the actual plot (such as it is).

My idea is that we encourage the writers to start using ChatGPT to write the jargon, even if it gets it wrong it wouldn’t be worse than what we have already so it is a win win. Plus since we all know that media tech works differently we don’t have to worry about the results being 100% accurate or correct.

One example is as below:

Forensic Scientist 1: Hey, have you seen the results from the trace DNA sample we collected from the crime scene?
Forensic Scientist 2: Not yet, I was just about to head over to the lab and check. Why, did you already receive them?
Forensic Scientist 1: Yeah, I just got an email from the lab. They’re pretty clear cut.
Forensic Scientist 2: Great, let’s take a look. What do the results show?
Forensic Scientist 1: Well, the sample is a match with the reference sample from our suspect. The lab confirmed a positive identification.
Forensic Scientist 2: That’s fantastic. Did they provide any details on the genetic markers?
Forensic Scientist 1: Yes, they identified several short tandem repeat markers that match between the sample and the reference. They also ran a mitochondrial DNA analysis and got a match there too.
Forensic Scientist 2: This is really strong evidence. But we need to be sure to double check all the details, especially since this is a high-profile case.
Forensic Scientist 1: Absolutely. I was thinking we should do a full review of the lab’s methodology and verify that the samples were handled and stored properly.
Forensic Scientist 2: That’s a great idea. Let’s also review the lab’s accreditation and see if they meet all the necessary standards.
Forensic Scientist 1: Right, we want to make sure our evidence is solid and can stand up in court.
Forensic Scientist 2: Definitely. Well, let’s head over to the lab and start our review.
Forensic Scientist 1: Sounds good. Let’s do it.

Another example:

Cybersecurity Professional 1: Hey, have you seen the alert about the recent cyberattack?
Cybersecurity Professional 2: Yes, I just received the notification. What do we know so far?
Cybersecurity Professional 1: The attack appears to be a phishing campaign. The attackers are using fake emails to steal login credentials from unsuspecting victims.
Cybersecurity Professional 2: That’s a common tactic. Did they manage to compromise any systems?
Cybersecurity Professional 1: Yes, we have reports of several systems being breached. Our incident response team is currently investigating the extent of the damage.
Cybersecurity Professional 2: Okay, let’s see if we can help with the investigation. What’s the first step?
Cybersecurity Professional 1: First, we need to isolate the infected systems and contain the spread of the attack. Then we can start looking into how the attackers gained access and what they did once they were in.
Cybersecurity Professional 2: Right. I’ll start working on the containment and isolation. Have you seen any indications of what the attackers are after?
Cybersecurity Professional 1: It’s not clear yet, but it looks like they are targeting sensitive information, such as financial data and personal information. We need to be proactive and make sure all our systems and data are secure.
Cybersecurity Professional 2: Agreed. We need to inform the relevant stakeholders about the attack and what measures we’re taking to prevent further damage.
Cybersecurity Professional 1: Absolutely. We also need to start preparing for the worst-case scenario, in case the attackers managed to exfiltrate any data.
Cybersecurity Professional 2: That’s a good point. We need to be prepared for the aftermath and make sure we have a plan in place to respond effectively.
Cybersecurity Professional 1: Right. Let’s get to work and make sure we minimize the impact of this attack.

What do you think?

– Suramya

November 14, 2022

IBM Unveils the worlds largest Quantum Computer with 433 qubits

Filed under: My Thoughts,Quantum Computing — Suramya @ 2:01 AM

Scaling up Quantum computers has become a race between the various players in the market and IBM has raised the stakes by unveiling a 433 qubits Quantum computer that is more than a 3x increase from their previous setup of 127 qubits. Even with this massive gain they are still ways off from a making a 4000 qubit computer by 2025 which is their goal.

In this new setup IBM replaced the “quantum chandelier” used in the previous processors with flexible ribbon cables that are designed for cryogenic environments. These new cables allow a more efficient flow of microwave signals which in turn decreased the interference caused by the cables. This gave them a 77% increase in the number of connections to the chip, which in turn enabled them to scale up more easily. They also separated the wires and components for control and readout into their own layers, which further reduced the interference with the qubits.

The new setup also includes a state of the art cryo-CMOS prototype controller chip implemented using 14-nanometer FinFET technology that reduces the power requirement for the setup from about 100 watts per qubit to about 10 milliwatts per qubit. The new beta update for Qiskit Runtime allows the user to trade speed for reduced error count and a new option called Qiskit primitives called a “resilience level” lets users dial in the cost/accuracy trade that is suitable to the task being worked on. Both functionality is expected to be ready for production release by 2025.

Quantum computing makes my head hurt but there is no doubt that it is changing the computing world in a massive way.

Source:
* IEEE Spectrum: IBM Unveils 433-Qubit Osprey Chip
* New Scientist: IBM unveils world’s largest quantum computer at 433 qubits

– Suramya

August 26, 2022

Using MultiNerf for AI based Image noise reduction

Filed under: Computer Software,Emerging Tech,My Thoughts,Tech Related — Suramya @ 2:58 PM

Proponents of AI constantly come up with claims that frequently don’t hold up to extensive testing, however the new release from Google Research called MultiNerf which runs on RAW image data to generate what the photos would have looked like without the video noise generated by imaging sensors seems to be the exception. Looking at the video it almost looks like magic, and appears to work great. Best of all, the code is open source and already released on GIT Hub under the Apache License. The repository contains the code release for three CVPR 2022 papers: Mip-NeRF 360, Ref-NeRF, and RawNeRF.

TechCrunch has a great writeup on the process. DIYPhotography has created a video demo of the process (embedded below) that showcases the process:


Video Credits: DIYPhotography

I like the new tools to make the photographs come out better, but I still prefer to take unaltered photos whenever I can. The most alteration/post-processing that I do on the photos is cropping and resizing. That also is something I do infrequently. But this would be of great use to professional photographers in conditions that are less than optimal.

– Suramya

August 6, 2022

Post Quantum Encryption: Another candidate algorithm (SIKE) bites the dust

Filed under: Computer Security,Computer Software,Quantum Computing — Suramya @ 8:23 PM

Quantum Computing has the potential to make the current encryption algorithms obsolete once it gets around to actually being implemented on a large scale. But the Cryptographic experts in charge of such things have been working on Post Quantum Cryptography/Post Quantum Encryption (PQE) over the past few years to offset this risk. SIKE was one of KEM algorithms that advanced to the fourth round earlier this year and it was considered as an attractive candidate for standardization because of its small key and ciphertext sizes.

Unfortunately while that is true researchers have found that the algorithm is badly broken. Researchers from the Computer Security and Industrial Cryptography group at KU Leuven published a paper over the weekend “An Efficient Key Recovery Attack on SIDH” (Preliminary Version) that describes a technique which allows an attacker to recover the encryption keys protecting the SIKE Protected transactions in under an hours time using a single traditional PC. Since the whole idea behind PQE was to identify algorithms that are stronger than the traditional ones this immediately disqualifies SIKE from further consideration.

Abstract. We present an efficient key recovery attack on the Supersingular Isogeny Diffie–Hellman protocol (SIDH), based on a “glue-and-split” theorem due to Kani. Our attack exploits the existence of a small non-scalar endomorphism on the starting curve, and it also relies on the auxiliary torsion point information that Alice and Bob share during the protocol. Our Magma implementation breaks the instantiation SIKEp434, which aims at security level 1 of the Post-Quantum Cryptography standardization process currently ran by NIST, in about one hour on a single core.

The attack exploits the fact that SIDH has auxiliary points and that the degree of the secret isogeny is known. The auxiliary points in SIDH have always been an annoyance and a potential weakness, and they have been exploited for fault attacks, the GPST adaptive attack, torsion point attacks, etc.

This is not a bad thing as the whole testing and validation process is supposed to weed out weak algorithms and it is better to have them identified and removed now than after their release as then it becomes almost impossible to phase out systems that use the broken/compromised encryption algorithms.

Source: Schneier on Security: SIKE Broken

– Suramya

May 27, 2022

Creating robots with no moving parts or computational ability which can navigate through mazes on their own

Filed under: Emerging Tech,Science Related — Suramya @ 11:34 PM

One would imagine that it takes skill or at least the ability to think to escape from a maze, unless you count running around like a headless chicken as a skill. However, Jie Yin and his colleagues at North Carolina State University have created a contraption that has no computational ability or moving parts but is still able to escape from a maze using trial and error.

The device is shaped like a pasta and is made from a rubber like material impregnated with liquid crystals. When this device is placed on a heated surface the parts in contact with the surface heat up and expand while the rest of the device remains the same this causes a twisting motion that allows it to roll at a speed of up to 3.8 millimetres per second. Even more interestingly this ‘robot’ can navigate a maze, when it reaches an obstacle such as a wall its orientation changes slightly and can sometimes continue moving. If that doesn’t work, then it continues to push against the obstacle which creates changes in the tension in the device allowing it to change the orientation of the arc’s on its surface to another direction, which would enable it to roll in the opposite direction. These two abilities enable it to continually change direction when meeting obstacles, bumping from surface to surface, eventually finding its way out despite lacking any intelligent control.

Autonomy is crucial for soft robotics that are constructed of soft materials. It remains challenging to create autonomous soft robots that can intelligently interact with and adapt to changing environments without external controls. To do so, it often requires an analogical soft “brain” that integrates on-board sensing, control, computation, and decision-making. Here, we report an autonomous soft robot embodied with physical intelligence for decision-making via adaptive soft body-environment interactions and snap-through instability, without integrated sensing and external controls. This study harnesses physical intelligence as a new paradigm for designing autonomous soft robots that can interact intelligently with their environments, thus potentially reducing the burdens on the conventional integrated sensing, control, computations, and decision-making systems in designing intelligent soft robots.

Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft body-obstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions.

This technology could be used to create cheap robots that can explore environments to take sensor readings and can potentially function inside the human body when made in microscopic scale. Since they don’t have any moving parts and don’t require power sources it would allow them to function for a longer duration than powered alternatives which would eventually run out of power. Plus, since they don’t require batteries it would be safer for people to ingest them without potentially harmful effects because most of the power sources in use today have some harmful chemicals in them.

The team’s findings have been published in the Proceedings of the National Academy of Sciences (PNAS) Journal: Twisting for soft intelligent autonomous robot in unstructured environments earlier this week.

Source: New Scientist: Pasta-shaped robot with no moving parts can navigate through mazes

– Suramya

« Newer PostsOlder Posts »

Powered by WordPress