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Is Tesla Entering Machine Learning As A Service Market?

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Tesla may be introducing machine-learning training as a web service with its upcoming'Dojo' supercomputer, CEO Elon Musk said on Twitter. Project Dojo was initially revealed by Musk last year and is a supercomputer which Tesla has been working on. The supercomputer has been designed to ingest massive amounts of video data and perform massive levels of unsupervised training on the visual data. The goal of Dojo will be to be able to take in vast amounts of data and train at a video level and do massive unsupervised training of vast amounts of video data. Dojo uses our own chips & a computer architecture optimized for neural net training, not a GPU cluster. Could be wrong, but I think it will be best in world.


An Introduction to AI

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I am Imtiaz Adam, and this article is an introduction to AI key terminologies and methodologies on behalf of myself and DLS (www.dls.ltd). This article has been updated in September 2020 to take into account advances in the field of AI with techniques such as NeuroSymbolic AI, Neuroevolution and Federated Learning. AI deals with the area of developing computing systems which are capable of performing tasks that humans are very good at, for example recognising objects, recognising and making sense of speech, and decision making in a constrained environment. Narrow AI: the field of AI where the machine is designed to perform a single task and the machine gets very good at performing that particular task. However, once the machine is trained, it does not generalise to unseen domains. This is the form of AI that we have today, for example Google Translate.


10 Exciting Webinars & Workshops In Machine Learning

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However, one of the ways professionals are keeping up their relevance in their organisations as well as in the industry is by upskilling and learning the latest tools and technologies of this evolving field. Webinars and workshops have always been an excellent way for professionals and enthusiasts to keep themselves updated with the latest trends and technologies. For attendees, these webinars and workshops are not only an easy way to know and train themselves on the latest tools and technologies but also allows them to hear from the best minds of the industry on relevant topics. In fact, for a few years now, large tech companies have been conducting free webinars and workshops, which will not only boosts the community and users at large but also acts as a great marketing tool for advertising their solutions and services. With machine learning being explored in various industries, including healthcare, eCommerce, finance and retail, the possibilities are endless.


Democratize AI: Exploring Future of Technology

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When individuals talk about artificial intelligence (AI), the first organizations that ring a bell are typically the FAANGs -- Facebook, Apple, Amazon, Netflix and Google. However, this is a long way from a complete rundown. Anybody can deploy AI today, and the FAANGs have no exceptional bit of leeway. The large technology companies accomplished early victories with artificial intelligence. Some even manufactured their own specific hardware, machine learning frameworks, and research and development centers.


Does Artificial Intelligence Keep Its Promises?

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Artificial Intelligence sounds freaking amazing: humanoid robots, artificial conscious, self learning systems and understanding the human brain. I won't lie; these were the things that motivated me to look into Artificial Intelligence. And till a certain extent they still do. I started out doing Physics and Life Sciences. One thing that caught my attention was the advancements in the field of so called "Artificial Neural Networks".


How can Artificial Intelligence innovate the way we socialise?

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Innovation in everything that we do is being driven by technology, including what we do on the internet. From social networking to our online searches, Artificial Intelligence assumes an undeniably significant role in studying our behaviour on digital media platforms and beyond. The greater part of the decisions we make in our day-to-day lives is mostly guided by AI-driven recommendations on our cell phones, personal assistants, chatbots, social network, or other AI technologies. Over 3.8 billion people are actively scrolling through one or the other social media platform such as Snapchat, LinkedIn, or YouTube at any given point of time. All these people and their conversations, searches, likes, dislikes, and more, are being thoroughly read to enable the machine to comprehend their preferences.


Pinaki Laskar posted on LinkedIn

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The #AI value chain, 1) AI chip and hardware makers who are looking to power all the AI applications that will be woven into the fabric of organisations big and small globally 2) The #cloud platform and infrastructure providers who will host the AI applications 3) The AI #algorithms and cognitive services building block makers who provide the vision recognition, speech and #deeplearning predictive models to power AI applications 4) Enterprise solution providers whose software is used in customer, HR, and asset management and planning applications 5) Industry vertical solution providers who are looking to use AI to power companies across sectors such as healthcare to finance 6) Corporate takers of AI who are looking to increase revenues, drive efficiencies and deepen their insights The today's AI is presented by what the BigTech and global social media platforms are pushing, it's Narrow /Weak AI /ML /DL, as "Cloud DL/AI Platforms". But this #Machinelearning algorithms are designed to optimize for a cost/loss function, having no intelligence, understanding or reasoning. So it is, Most curve-fitting AI tools available today sold as focused on predicting, identifying, or classifying things, a rote "learning from data/experience".


IBM Joins Effort by UN and Vatican to Use Ethical AI in Fight Against Hunger

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The Vatican's Pontifical Academy for Life, which began the year by urging the ethical development and application of artificial intelligence (AI), has announced an effort to use technology to fight world hunger, which has worsened during the pandemic. The Vatican institution, in collaboration with IBM, Microsoft and the UN Food and Agriculture Organization, or FAO, is encouraging governments, nonprofits and corporations to assure that technology is used to feed everyone, and to make farmers' lives more efficient and productive. In its quest to assure the transparent, responsible and inclusive use of AI, the Vatican and FAO are pushing for solutions in agriculture that will benefit not just the well off, but also the poor. "We need to face the biggest challenges on the planet," said John E. Kelly III, executive vice president of IBM. Kelly, who participated in the FAO and Pontifical Academy's Sept. 24 virtual conference announcing the effort against hunger, was one of the signers of the Vatican's call for AI ethics in February. The Vatican's effort to promote ethical AI for social good includes a new program to use digital technology to ensure a more sustainable and efficient global food supply.


At CAGR 36.2%, Artificial Intelligence Market 2020: Future Challenges And Industry Growth Outlook 2025

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Artificial Intelligence (AI) is the study of "intelligent agents" which can be define as any device that perceives its environment and takes appropriate action that makes the highest probability of achieving its goals. Additionally, it can also be define as a system's ability to interpret external data, learn from gathered data and use those learnings to realize specific goals through adaptation. It is also called as machine intelligence and attributed to the nature of intelligence demonstrated by machines. Some of the features of artificial intelligence are; successfully understanding human language, contending at the highest level in strategic games systems such as chess and go, autonomously operating cars, intelligent routing in content delivery networks and military simulations and others. To solve the problem of learning and perceiving the immediate environment, many approaches have been taken such as statistical methods, computational intelligence, versions of search and mathematical optimization, artificial neural networks, and methods based on statistic, probability and economics.


Vision Processing Units (VPUs)

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On my first day working for MILLA, an autonomous shuttle company, I discovered a shuttle that can drive up to 30 km/h; quite an improvement if you compare it to our competitors at the time driving at 5–8 km/h. At the time, the shuttle was new and there was no GPU yet on it. In case you don't know what a GPU is, here's a quick picture that explains it well: A GPU (Graphic Processing Unit) parallels the processes so operations are done faster. In a self-driving car, this can be super useful for computer vision or point cloud processing. It was first released in video games because of the need to display multiple things at the same time.