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World Economic Forum.
They’re autonomous, self-cleaning and powered entirely by solar energy.
ECHO, the robot, belongs to the Woods Hole Oceanographic Institution and rolls around the tundra collecting data used to study marine ecosystems.
The small robot takes readings and collects data like a normal researcher, but his existence allows researchers to collect real-time information year round and minimize the impact their presence could have on the animals’ lives.
Researchers say the penguins seem to be getting along swimmingly with the robot.
Eleuther AI developed GPT Neo, an open-source model, an autoregressive transformer using the mesh library.
Elon talks about x-risks and making us a multi-planetary species, amongst other things.
What’s on Elon Musk’s mind? In this exclusive conversation with head of TED Chris Anderson, Musk details how the radical new innovations he’s working on — Tesla’s intelligent humanoid robot Optimus, SpaceX’s otherworldly Starship and Neuralink’s brain-machine interfaces, among others — could help maximize the lifespan of humanity and create a world where goods and services are abundant and accessible for all. It’s a compelling vision of a future worth getting excited about. (Recorded at the Tesla Texas Gigafactory on April 6, 2022)
One key aspect of intelligence is the ability to quickly learn how to perform a new task when given a brief instruction. For instance, a child may recognise real animals at the zoo after seeing a few pictures of the animals in a book, despite any differences between the two. But for a typical visual model to learn a new task, it must be trained on tens of thousands of examples specifically labelled for that task. If the goal is to count and identify animals in an image, as in “three zebras”, one would have to collect thousands of images and annotate each image with their quantity and species. This process is inefficient, expensive, and resource-intensive, requiring large amounts of annotated data and the need to train a new model each time it’s confronted with a new task. As part of DeepMind’s mission to solve intelligence, we’ve explored whether an alternative model could make this process easier and more efficient, given only limited task-specific information.
Today, in the preprint of our paper, we introduce Flamingo, a single visual language model (VLM) that sets a new state of the art in few-shot learning on a wide range of open-ended multimodal tasks. This means Flamingo can tackle a number of difficult problems with just a handful of task-specific examples (in a “few shots”), without any additional training required. Flamingo’s simple interface makes this possible, taking as input a prompt consisting of interleaved images, videos, and text and then output associated language.
Similar to the behaviour of large language models (LLMs), which can address a language task by processing examples of the task in their text prompt, Flamingo’s visual and text interface can steer the model towards solving a multimodal task. Given a few example pairs of visual inputs and expected text responses composed in Flamingo’s prompt, the model can be asked a question with a new image or video, and then generate an answer.
0:00 PeopleLens AI Helps The Blind.
1:40 Brain Fingerprints Detect Autism.
4:52 AI Predicts Cancer Tumor Regrowth.
Learn more about the future of decentralized AI here:
SingularityNET AGIX Website — https://singularitynet.io
Developer Documentation — https://dev.singularitynet.io/
Publish AI Services — https://publisher.singularitynet.io/
AGIX Community Telegram — https://t.me/singularitynet
AGIX Price Chat Telegram — https://t.me/AGIPriceTalk
HPE has launched its Swarm Learning and Machine Learning Development System whilst Salesforce announced further integration with Slack, Tableau, and Mulesoft.
Calculator is also more smart than humans but it made our life easier.
While the win over Google’s AI was impressive, more advanced developments are being made behind the scenes as well. The integration of multiple AIs, called neural networks, has led to computers with unique personalities and quirks that were previously only seen in humans.
AI is already outsmarting humans
Continue reading “Artificial Intelligence Is Already Outsmarting Humans!” »
“Pressure and mobility have an inverse relationship,” Diaz Artiles said. “The more pressure you have in the spacesuit, the lower the mobility. The less pressure you have, the easier it is to move around.”
“Imagine wearing really tight Under Armour or really tight leggings. That pressure pushing down on your body would be in replace of or in addition to gas pressure,” Kluis said. “So the idea with the SmartSuit is that it would use both mechanical pressure and gas pressure.”
Diaz Artiles and her team continue to work on the SmartSuit architecture, and the actuator prototypes are a promising development in creating a more accommodating and resourceful spacesuit for future planetary missions. Their end goal would be for it to feel like the wearer is moving without the spacesuit on and without breaking too much of a sweat.
Making the future of medicine possible by rethinking how medicines are made — olivia zetter, head of government affairs & AI strategy, resilience.
Olivia Zetter is Head of Government Affairs and AI Strategy at National Resilience, Inc. (https://resilience.com/) a first-of-its-kind manufacturing and technology company dedicated to broadening access to complex medicines and protecting bio-pharmaceutical supply chains against disruption.
