NASA Wants Spaceships to Communicate With Astronauts Via Chatbot

Want to see the details of implementation of data integration hwew.

NASA Wants Spaceships to Communicate With Astronauts Via Chatbot

The agency's proprietary program will spot, communicate, and fix errors from space, beginning with the Artemis program’s Lunar Gateway.

By Adrianna Nine June 27, 2023

Chatbots are making their way into other corners of the solar system. As ChatGPT, Bard, and other artificial intelligence-powered chatbots find their way into virtually every industry here on Earth, NASA is considering bringing its own version of the technology aboard spacecraft. The proprietary interface will reportedly facilitate communications with crewmembers, beginning with the Artemis program’s Lunar Gateway.

Dr. Larissa Suzuki, a visiting researcher at NASA, announced the project at the Institute of Electrical and Electronics Engineers (IEEE) on Tuesday. The plan is to build a network capable of fielding interplanetary communications while using AI to spot and fix errors as they occur. The program—the name of which has yet to be shared with the public—will effectively work as a virtual repairman, diagnosing errors and inefficiencies and then resolving them (or, at the very least, suggesting potential fixes) when it’s impractical to perform hands-on work. 

NASA intends for the program to be easy to use. Like ChatGPT, space-bound astronauts and crewmembers down on Earth can “talk” with NASA’s program, precluding the need for complicated manuals or tiresome back-and-forth conversations with parties that aren’t directly involved. If NASA can incorporate federated learning—a collaborative approach to training deep learning models—into its interface, it could even have multiple spacecraft share their knowledge, helping the fleet locate important geology or reduce downtime up in space.    ... ' 

AI Might Enable Us to Talk to Animals Soon. Here's How

Have my doubts.

Home/News/AI Might Enable Us to Talk to Animals Soon. Here's.../Full Text

ACM NEWS

AI Might Enable Us to Talk to Animals Soon. Here's How.  By ZDNet, May 5, 2023

Through machine learning techniques, we could gain the power to decipher collected bioacoustic data and translate it into natural human languages.

Imagine listening to chirping birds and being able to pull out your phone and decipher what they're saying to each other. Then picture yourself going on a safari in Africa and following a conversation between a pair of elephants. Think that sounds farfetched? Think again: It's actually part of the tech-enabled future the Earth Species Project (ESP) wants to build.

The ESP is a nonprofit founded by Mozilla Labs cofounder, Aza Raskin, and Britt Selvitelle, a member of the Twitter founding team, and it's leading the charge towards decoding non-human communication using artificial intelligence (AI).

Being able to understand your cat's innermost thoughts sounds fascinating. But the benefits of understanding animals go way beyond listening into a conversation between your dog and its canine buddies when they're out on a walk. 

In fact, the ability to decipher animal communication has direct implications for conservation and the protection of our planet.

From ZDNet

View Full Article      https://www.zdnet.com/article/ai-might-enable-us-to-talk-to-animals-soon-heres-how/  

Rephrasing Communications in Context

 Advances in assistant communications.  In Google Blog,  As always context is very important. 

Contextual Rephrasing in Google Assistant

Tuesday, May 17, 2022

Posted by Aurelien Boffy, Senior Staff Software Engineer, and Roberto Pieraccini, Engineering Director, Google Assistant

When people converse with one another, context and references play a critical role in driving their conversation more efficiently. For instance, if one asks the question “Who wrote Romeo and Juliet?” and, after receiving an answer, asks “Where was he born?”, it is clear that ‘he’ is referring to William Shakespeare without the need to explicitly mention him. Or if someone mentions “python” in a sentence, one can use the context from the conversation to determine whether they are referring to a type of snake or a computer language. If a virtual assistant cannot robustly handle context and references, users would be required to adapt to the limitation of the technology by repeating previously shared contextual information in their follow-up queries to ensure that the assistant understands their requests and can provide relevant answers.

In this post, we present a technology currently deployed on Google Assistant that allows users to speak in a natural manner when referencing context that was defined in previous queries and answers. The technology, based on the latest machine learning (ML) advances, rephrases a user’s follow-up query to explicitly mention the missing contextual information, thus enabling it to be answered as a stand-alone query. While Assistant considers many types of context for interpreting the user input, in this post we are focusing on short-term conversation history.

Context Handling by Rephrasing

One of the approaches taken by Assistant to understand contextual queries is to detect if an input utterance is referring to previous context and then rephrase it internally to explicitly include the missing information. Following on from the previous example in which the user asked who wrote Romeo and Juliet, one may ask follow-up questions like “When?”. Assistant recognizes that this question is referring to both the subject (Romeo and Juliet) and answer from the previous query (William Shakespeare) and can rephrase “When?” to “When did William Shakespeare write Romeo and Juliet?”

While there are other ways to handle context, for instance, by applying rules directly to symbolic representations of the meaning of queries, like intents and arguments, the advantage of the rephrasing approach is that it operates horizontally at the string level across any query answering, parsing, or action fulfillment module.  ... '

Laser Space Communications Sat to be Launched

 New aims to improve solar system wide communications.

How NASA's new laser communications mission will work in space    in Space.com

By Elizabeth Howell about 5 hours ago

The goal is to speed up solar system communications.

A "data hunger" in space is driving the launch of a new laser communications mission, a NASA official told Space.com.

The Laser Communications Relay Demonstration will launch on the United States Space Force Space Test Program 3 (STP-3) mission no earlier than Dec. 5 at 4:04 a.m. EST (0904 GMT). You can watch the rocket launch Sunday online courtesy of United Launch Alliance, which is flying the mission on an Atlas V rocket.

"This will be our first foray into understanding, what does it mean to use lasers to communicate and really connect directly to Earth and space users?" Jason Mitchell, Director of SCaN Advanced Communications & Navigation Technology Division at NASA, told Space.com in a recent video interview.

LCRD will help NASA learn about possible effects to manage, ranging from atmospheric turbulence to cloud deflection, Mitchell noted. The timing is crucial as NASA and its international partners expand its exploration focus over the coming decades.

Newly announced private space stations will only expand the need for fast information flowing to and from Earth. Meanwhile, astronauts on the moon and a sample return mission on Mars could benefit from faster communications speeds 10 to 100 times faster than current-day radio.

LCRD and forthcoming laser demonstrations a little further from Earth, Mitchell said, will help figure out how to operate lasers from a hub such as a moon base. In turn, he said, the "learning experience at the moon [will show] how we would look to operate this at Mars — as well as in any other location, really, in space where you have a central spot that you really want to collect a lot of data from."

LCRD will operate from geosynchronous orbit at 22,236 miles (35,786 kilometers) to test out laser communications for at least two years. The demonstration is meant to demonstrate the sustainability of longer space missions after several brief, successful attempts to try laser comms in space. 

Making sure the mission outlasted the stresses of launch and space radiation for years, instead of a few weeks of months, was top of mind during the design process, Mitchell said.  ... ' 

Detecting Sarcasm

 Computers Detecting Sarcasm  An important component of modern communication

How Computers Can Finally Detect Sarcasm Ramya Akula and the tech that lets sentiment analysis spot mocking words3119:2901 JUL 2021.   Podcast and transcript 

Hi and welcome to Fixing the Future, IEEE Spectrum’s podcast series on the technologies that can set us on the right path toward sustainability, meaningful work, and a healthy economy for all. Fixing the Future is sponsored by COMSOL, makers of of COMSOL Multiphysics simulation software. I’m Steven Cherry.

Leonard: Hey, Penny. How’s work?

Penny: Great! I hope I’m a waitress at the Cheesecake Factory for my whole life!

Sheldon: Was that sarcasm?

Penny: No.

Sheldon: Was that sarcasm?

Penny: Yes.

Steven Cherry That’s Leonard, Penny and Sheldon from season two of the Big Bang Theory. Fans of the show know there’s some question of whether Sheldon understands sarcasm. In some episodes he does, and in others he’s just learning it. But there’s no question that computers don’t understand sarcasm or didn’t until some researchers at the University of Central Florida started them on a path to learning it. Software engineers have been working on various flavors of sentiment analysis for quite some time. Back in 2005, I wrote an article in Spectrum about call centers automatically scanning conversations for anger either by the caller or the service operator. One of the early use cases behind messages like this call may be monitored for quality assurance purposes. Since then, software has been getting better and better at detecting joy, fear, sadness, confidence and now, finally, sarcasm. My guest today, Ramia Akula, is a PhD student and a graduate research assistant at the University of Central Florida is Complex Adaptive Systems Lab.. She has at least 11 publications to her name, including the most recent interpretable multiheaded self attention architecture for Sarcasm Detection in Social Media, published in March in the journal Entropy with her advisor, Ivan Garibay Ramia. Welcome to the podcast.   ... ' 

Detecting Sarcasm

Even in the early days of reading consumer reactions to product communications  we knew it was useful to have an idea of how much sarcasm was being used.  To determine human reactions to statements or images.   Often we just scrubbed potential sarcasm. but we knew we were losing something by not analyzing it.

This work on Detecting Sarcasm  also Discussed in  VentureBeat  

Modeling Intra and Inter-modality Incongruity for Multi-Modal Sarcasm Detection

By Hongliang Pan, Zheng Lin, Peng Fu, Yatao Qi, Weiping Wang

Abstract

Sarcasm is a pervasive phenomenon in today’s social media platforms such as Twitter and Reddit. These platforms allow users to create multi-modal messages, including texts, images, and videos. Existing multi-modal sarcasm detection methods either simply concatenate the features from multi modalities or fuse the multi modalities information in a designed manner. However, they ignore the incongruity character in sarcastic utterance, which is often manifested between modalities or within modalities. Inspired by this, we propose a BERT architecture-based model, which concentrates on both intra and inter-modality incongruity for multi-modal sarcasm detection. To be specific, we are inspired by the idea of self-attention mechanism and design inter-modality attention to capturing inter-modality incongruity. In addition, the co-attention mechanism is applied to model the contradiction within the text. The incongruity information is then used for prediction. The experimental results demonstrate that our model achieves state-of-the-art performance on a public multi-modal sarcasm detection dataset. ... 

Secure Quantum Communications

Intriguing application of quantum communication.  Reminds me me some papers read in the way back about use of split wavelength data streams.    Worth a look. 

Secure Quantum Communications Network the Largest of Its Kind
New Scientist
Chris Stokel-Walker
September 2, 2020

Scientists at the U.K.'s University of Bristol have developed a secure quantum communications network based on multiplexing entanglement, a process that can be used to produce a secure encryption key. Multiplexing entanglement splits photons from a single laser based on their wavelength, rather than linking users one-to-one. Bristol's Siddarth Joshi said each wavelength can support a data stream, allowing the system to accommodate 50 to 100 users with existing hardware. Joshi says this method can be used to link millions of devices together, and his goal "is to build the quantum Internet."... '

AI Agents Learning to Communicate

Machines learning and adapting using language.   As suggested,the environment/context is also important.

AI agents can learn to communicate effectively  by University of Gothenburg

A multi-disciplinary team of researchers from Chalmers and University of Gothenburg has developed a framework to study how language evolves as an effective tool for describing mental concepts. In a new paper, they show that artificial agents can learn how to communicate in an artificial language similar to human language. The results have been published in the scientific journal PLOS ONE.

This research lies on the border between cognitive science and machine learning. There has been an influential proposal from cognitive scientists that all human languages can be viewed as having evolved as a means to communicate concepts in a near-optimal way in the sense of classical information theory. The Gothenburg researchers' method for training the artificial agents is based on reinforcement learning, which is an area of machine learning where agents gradually learn by interacting with an environment and getting feedback. In this case, the agents start without any linguistic knowledge and learn to communicate by getting feedback on how well they succeed in communicating a mental concept.

Reconstructing colors

"In our paper we have studied how agents learn to name mental concepts and communicate by playing a several rounds of a referential game consisting of a sender and a listener. We have especially focused on the color-domain which is well studied in cognitive science. The game works as follows; the sender sees a color and describes it by uttering a word from a glossary to the listener which then tries to reconstruct the color.

Both agents receive a shared reward based on how precise the listener's reconstruction was. The words in the glossary have no meaning at the outset; it is up to the agents to agree on the meaning of the words during multiple rounds of the game. We see that the resulting artificial languages are near-optimal in an information-theoretic sense and with similar properties as found in human languages," says Mikael Kågebäck, researcher at Sleepcycle, and whose Ph.D. dissertation at Chalmers contained some of the results presented in the paper. .... " 

Cognixion: Unlocking Speech

Was reminded today of Cognixion,  formerly Smartstones,  and founder Andreas Forsland, which I have a connection with.  Their site features a system called: Speakprose :    " Giving Voice  Speakprose empowers people with communication challenges to achieve an independent life and truly engage with the world.  ... "   You can try it from the link, about to.

They further write about Cognixion,

AI-Powered People
Cognixion is a team of visionary technologists, researchers and designers focused on creating products that accelerate and enrich human communication and physical capabilities. .... 

Our Mission Matters
Cognixion is a mission-driven company, aiming to unlock speech for hundreds of millions of people worldwide affected by communication disabilities. By providing affordable and accessible technologies that are powered by AI (artificial intelligence), the world will look and feel very different in the next decade. We will be interacting with far more AI-Powered People at school, at work and on the go. Imagine a world where there are thousands of creators, scientists, artists, engineers, change-makers and philosophers just like Stephen Hawking, contributing to society now that they have a voice.

Areas of Focus
We build upon and create sound science, cutting-edge technologies and natural interfaces for accessing the world in new ways.

● AI-POWERED NEURAL INTERFACES
Our wireless BCI (brain computer interface) technology optimizes the signals from each user's unique brain and can be fitted to any head shape. By reading brain signals alone, our BCI solution detects attention toward an object that represents the intended speech.

● ARTIFICIAL INTELLIGENCE
Our advanced machine learning algorithms adapt to the nuances in how users interact with our technology. With each use, our technology gets smarter and more efficient at recognizing, and even predicting what the user intends to communicate.

● AUGMENTED REALITY
We enable users to simultaneously interact with their physical environment and the overlaid digital world. As they select an object in AR to indicate their intended speech, we personalize communication options according to the user's current context and adapt the AR system based on changing environments.

● APPLIED NEUROSCIENCE
We create solutions based on behavioral and brain science to support learning and operation. Our structured digital environments are motivating, easy to use, and quickly develop new capabilities.

● FOSTERING HUMAN CAPABILITIES
We build on whatever abilities are available – hearing, touch, gesture, movement, or even simply attention to the environment – as we design interfaces to enable nonverbal individuals communicate their intentions.

● BEHAVIORAL BENEFITS & SOCIAL IMPACT
We improve quality of life and create economic impact. Easier access to communication for the nonverbal individual means reductions in frustration, isolation, and costly behavioral interventions. Their newfound independence and social inclusion leads to new opportunities to close the equity gap. ... " 

Considering the Length of Lists

Very nicely put pieee on the length of lists.  Very true., good to have in the back of your mind when writing or speaking.

Communicate Using the Numbers 1, 2, 3, and More    By Thomas A. Limoncelli

Communications of the ACM, June 2020, Vol. 63 No. 6, Pages 42-44   10.1145/3386267

The human brain reacts differently to lists of different lengths. When you align what you say with what the human brain expects, you communicate more effectively. In this column I'll explain how to leverage the way the brain reacts to various quantities to make your speaking and writing more effective.

People often use lists of various sizes when communicating. I might have 2 reasons for supporting the new company strategy. I might tell you my 3 favorite programming languages. I might make a presentation that describes 4 new features. There is 1 vegetable that I like more than any other.

The length of the list affects how the audience interprets what is being said. Not aligning with what the human brain expects is like swimming upstream. Given the choice, why would anyone do that?  ... '