If AI Art generators are inserted into a robot, it can do wonders, here is an example.
If you’ve been hanging out on Twitter lately, then you’ve probably noticed a profusion of AI-generated images sprouting all over your timeline like weird, algorithmic visions. These pictures have been generated using a new app called Dream, which lets anyone create “AI-powered paintings” by simply typing a brief description of what they want to see. It’s odd, often uncanny stuff- and extremely fun.
The resulting artwork has its own particular aesthetic, defined by swirling shapes and incoherent objects. The real magic, though, is that no matter what you type, the app will generate something visually compelling (at least until we get too used to these toys) and that matches your prompt in often surprisingly opposite ways.
UK-based robotics company Engineered Arts just gave an ultra-realistic-looking humanoid robot Ameca a voice. Ameca is the world’s most advanced human-shaped robot representing the forefront of human-robotics technology. In a new video, the company showed off Ameca having a conversation with a number of the company’s engineers, courtesy of a speech synthesizer and OpenAI’s GPT 3, a cutting-edge language model that uses deep learning to generate impressively human-like text.
It seems it is and it’s an impressive demonstration of the power of cutting-edge robotics. Perhaps what’s most noteworthy about the video is that now the robot also moves the parts below its head. Something it did not do in the first video.
It can be seen gesturing its hand around in what seems like a very realistic movement. There’s no doubt about it, when it comes to mimicking humans Ameca is a pro!
In their video, Engineered Arts also took a swipe at Tesla’s unsuccessful attempt to build a humanoid robot. In the background, a person can be seen watching a video featuring the Tesla dancer that was subbed in for an actual humanoid robot.
Specialty of the Robot
The company Engineered Arts says that Ameca is the “world’s most advanced human-shaped robot” which would represent “the forefront of human-robotics technology”. It further says that Ameca is “the perfect humanoid robot platform for human-robot interaction” and is based on technologies that are reliable, modular, upgradeable, and easy to develop. Interestingly, each module of the robot can function independently, meaning you don’t need a fully assembled robot and can only use its head or even a single arm.
The cloud-connected focus feature of the robot, which would allow its owners to control it as a personal avatar, animation, and simulation, is another interesting feature. Powered by the Tritium operating system, the company says that Ameca is basically a subject where artificial intelligence and machine learning systems can be tested. “Ameca gives us a glimpse of the future and provides a reliable hardware platform to develop new AI and machine learning technologies”, the company said.
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Top 10 AI Universities Leading In Research And Innovation In 2023
Here are the top 10 AI universities engaged in research and innovation in 2023
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. AI research is the field of study of intelligent agents, which refers to any system that perceives its environment and takes actions that maximize its chance of achieving its goals. A professional degree in AI from a reputed university will help you get started in this AI industry. It has signified a great number of developing technologies including robotics, IoT, and big data. Here are the top 10 AI universities engaged in research and innovation in 2023.
Harvard University opened the Lawrence Scientific School as its first formal effort to provide higher-level education in engineering and the sciences. Under the category of Computer Science, Artificial Intelligence and the subsets of Computational Linguistics, Machine Learning, Multi-agent Systems, and Robotics, are researched in detail by various faculty members.
Standford University ranks #2 on Nature’s Index for top academic institutions in AI. The Stanford Artificial Intelligence Laboratory is set up to advance knowledge and foster learning. The lab team is always working on new AI research projects like the MetaMorph model and task-specific fine-tuning for robotics.
Carnegie Mellon University:
Carnegie Mellon University is frequently heard of in the AI research community. CMU’s research leads in upcoming AI concepts of self-driving cars, speech recognition, advanced sensor design, facial recognition software, and more. CMU has worked on several projects, including five interactive maps, etc.
The Massachusetts Institute of Technology is known for its MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), the lab has housed some of the top researchers and won several awards, and mentored leaders that have gone ahead to create notable innovations.
University of California Berkeley:
UC Berkeley is consistently ranked among the five top research universities globally with an AI research unit. The Berkeley Artificial Intelligence Centre lab includes ML, NLP, planning, control, and robotics.
Cornell University is ranked fourth in the world for research in engineering. Cornell’s research is conducted in several areas like robotics, NLP, vision, ML, and interdisciplinary topics related to AI.
Vellore Insititute of Technology:
The school of computer science at Vellore Insititute of Technology has more than 1500 publications. It aims to further apply research in computer science and offers Ph.D. courses. The team of VIT students and alumni worked on the prevalent XOR problem and found a solution.
Indian Institute of Technology, Bombay:
The IIT Bombay research lab, Center for Indian Language Technology, the department offers Ph.D. programs in computer science and is one of the most well-known for its AI research. The latest research like Breaking the trial-and-error loop in Material Design through Machine Learning and ‘Computational techniques to measure small amounts of soot.
Indian Institute of Technology, Delhi:
IIT-D is among the top five IITs and encourages AI research in India. The university opened the School of Artificial Intelligence center for Ph.D. programs to multiply research productivity. IIT-D also houses a research group, Data Analytics & Intelligence Research, to build AI applications for India.
Indian Institute of Technology, Madras:
IIT-M has developed Ai4Bharat, an NLP model to process eleven regional languages, and the Robert Bosch Centre for Data Science and Artificial Intelligence was introduced to further AI research. The research applications focus on addressing Indian issues and leveraging AI for local, vernacular, healthcare, and agricultural problems.
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DCNN’s Vision Incapability Could Put Real-World AI Apps In Danger
AI is currently facing several complex challenges that might jeopardize the existing models
Artificial intelligence has become the largest innovation that the tech industry has ever witnessed. The innovation and research directed by AI are aiding global industries like healthcare, retail, and finance toward advancements. Even though evolving technology has become an important element in business development, AI is bringing new perspectives to the global entrepreneurial paradigm with its avant-garde approaches. AI applications and models are being deployed by some of the major tech companies in the world like Amazon, Apple, Facebook, and IBM. These companies constantly evolve their AI integration pipeline based on the evolving tech landscape. AI’s most important and gradually advancing branch is deep learning since the importance of convolutional neural networks has become quite evident to business leaders.
The growing demand for deep neural networks and deep convolutional neural networks has forced researchers and scientists to advance their prospects. But unfortunately, after several rapid advancements, convolutional deep neural networks or DCNNs still do not possess the same accuracy as humans do, and since AI is literally supposed to automate and perform tasks for humans, AI neural networks need accuracy and efficiency to imitate human intelligence. According to recent reports, DCNNs do not envision objects the way humans do and this could prove to be quite dangerous for the AI applications that are already being deployed in projects.
Deep Convolutional Neural Networks have Failed to Attain Sensitivity like Humans
In a collaborative study conducted by Elder, from York Research Chair in Human and Computer Vision and the Co-Director of York’s Centre for AI and Society, and Assistant Psychology professor Nicholas Baker from Loyola College in Chicago explores how human brains and DCNNs react to ‘Frankensteins’, a novel visual stimuli. Frankensteins are basically simple objects that have been taken apart and put back together, in the wrong way. Generally, when presented with a Frankenstein object, humans get confused, whereas, DCNNs do not reveal any insensitivity to these configural object properties.
The researchers claimed that the streamlining of these AI models has failed under certain critical conditions and clearly demonstrate that AI development should focus more on tasks beyond object recognition. Apparently, these models use “shortcuts” while solving complex recognition tasks. Sometimes these shortcuts work, based on several cases, but unfortunately, these might become quite dangerous when it comes to real-world AI applications that the industry and government are currently using.
Based on the predicaments released by researchers, modifications to the training and architecture of AI models can make these neural network projects act more as the human brain would usually do. They speculate that to accurately match human configural sensitivity, all networks should be trained to solve a broader range of cutting-edge tasks which goes beyond object recognition. In a nutshell, these are the basic shortcomings that AI researchers should work on overcoming. AI is not just a technology that can be used to automate complex human tasks, it was innovated for human intelligence, it might sound dangerous, but scientists should now focus on meeting complex challenges to successfully attain these goals.
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AI Is Not Just Your Best Friend But Is A Mirror To Your Soul
Psychologists say that the growing involvement of AI and the adjoining digital technologies has stunted the mental growth of today’s youth. Young people, who were earlier connected with each other socially and physically are now only connected digitally, indicating high reports of loneliness. The depression rate is higher among teenagers and millennials who spend a massive amount of working towards building a career and only focus on digital interaction. But the actual debate is that since AI is the problem, AI is also the solution.
The emergence of AI friends or AI companions has truly changed the dynamics of friendship and social interaction. But these AI friend applications are not just your friends, but are a mirror to your soul. Users get permission to customize the AI avatar to whoever and however, they like. AI companions reassure users by asking questions about how they are as if they are really interested and always try to give an answer that fits into the context of the conversation.
We can take the Replica AI application, for example. It’s a personalized chatbot that learns to replicate the text patterns and personality of the user who created it, almost like a best friend, who is always on point. Replika provides investors with the ability to choose personality traits, and interests, and change the nature of the relationship like friend, girlfriend, mother, sister, and mentor. Users can also give a realistic-seeming voice call to their Replica buddy. Well, the whole concept of Replica truly reflects that AI friends are just proper mirrors to what the soul actually wants, with only minor room for error.
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