Investors Bet Flex Logic embedded FPGAs will catch Edge AI wave with $55M new funding

Geoff Tate, CEO and cofounder of Flex Logix Technologies, told us several years back that edge AI inferencing would be the embedded FPGA vendor’s biggest market through about 2023. Among the reasons was the crying need for an affordable inference engine that could also handle a range of applications as data processing and storage shifts from cloud data centers to edge devices.

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Model Scaling that’s both accurate and fast: Facebook AI…

The past several years have seen the rapid development of new hardware for training and running convolutional neural networks. Highly-parallel hardware accelerators such as GPUs and TPUs have enabled machine learning researchers to design and train more complex and accurate neural networks that can be employed in more complex real-life applications.

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Trending toward concept Building – A review of Model Interpretability for Deep Neural Networks

Explaining how deep neural networks work is hard to do. It is an active area of research in academia and industry. Data scientists need to stay current in order to create models that are safe and usable. Leaders need to know how to avoid the risk of unethical, biased, or misunderstood models. In this post, I breakdown trends in network interpretability applied to image data. Some of the approaches covered apply to non-image-based networks as well. 

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Artificial Intelligence (AI) and Prosthetics: The new frontier

AI Prosthetics

If you’ve found your way to this little part of the internet — then you obviously either love robotics, have played way too much Deus Ex: Human Revolution, or are just an avid technophile like myself who is fascinated by science, computers and how they are forging new paths toward a bionic future.

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Federated Learning: A decentralized form of Machine Learning

Most major consumer tech companies that are focused on AI and machine learning now use federated learning – a form of machine learning that trains algorithms on devices distributed across a network, without the need for data to leave each device. Given the increasing awareness of privacy issues, federated learning could become the preferred method of machine learning for use cases that use sensitive data (such as location, financial, or health data).

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Tesla Working on Full Self-Driving Mode, Extending AI Lead 

Tesla Model car

Tesla’s goal to release its level 5 Full Self Driving (FSD) mode autopilot capability in 2021 was deemed unrealistic by the CEO of competitor Waymo in a recent interview.  Tesla is the only autonomous vehicle manufacturer using real-time cameras, rather than pre-mapped Lidar (Light Detection and Ranging) to guide vehicle movement. Tesla also…

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Why Is Object Detection So Messy?

Object Detection

Those working with Neural Networks know how complicated Object Detection techniques can be. It is no wonder there is no straight forward resource for training them. You are always required to convert your data to a COCO-like JSON or some other unwanted format. It is never a plug and play experience. Moreover, no diagram thoroughly explains Faster R-CNN or YOLO as there is for U-Net or ResNet. There are just too many details.

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Neural Networks In a Nutshell

I will try my level best to present a transparent view of how neural network works such that by the end of this article you might gain a solid knowledge of this topic. Since machine learning algorithms are now recursively used to predict various cases like cancer , stocks etc. the number of neural networks projects are growing at an exponential rate. We can also say that neural networks sits at the core of revolutionary machine learning projects.

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What is Artificial Intelligence? How does AI work, types and the future of it?

Head

The intelligence demonstrated by machines is known as Artificial Intelligence. Artificial Intelligence has grown to be very popular in today’s world. It is the simulation of natural intelligence in machines that are programmed to learn and mimic the actions of humans. These machines are able to learn with experience and perform human-like tasks. As technologies such as AI continue to grow, they will have a great impact on our quality of life.

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Retraining Machine Learning Model approaches

Typewriter and items

Generally machine learning models will be trained by some learning between set of input features and dependent feature or target variable. The aim of the model is to minimize the prediction error by applying or optimizing cost functions, and when we found some optimized models, we will deploy into the production and the aim is that model will generate accurate predictions on future unseen data as well so the goal is that model will predict the future unseen data as accurately as data used during the training period.

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IBM AI helps to break down massive code to ease cloud migration

Cloud technology has certainly brought along more convenience, enabling anyone to access their photos, email and other applications anywhere and at anytime. But not all companies have moved everything to the cloud just yet. Those looking to migrate typically have to break down their apps into smaller chunks in a process dubbed refactoring — or restructuring their computer code without changing its intended functions.

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How to train a neural network from scratch

In this article, I will continue our discussion on artificial neural networks, and give an example of a very simple neural network written in python. The purpose of this series of articles I am writing is to give a full explanation of ANN’s from the ground up, with no hiding behind special libraries. Tensorflow is great for prototyping and production, but when it comes to education the only way to learn is to get a pencil and paper and get dirty in math.

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Peeking into AI’s ‘black box’ brain — with physics

Cats aren’t dogs. Even modern AI knows that. But how exactly AI distinguishes cat images from those of dogs is not clear. Standard neural networks are akin to a black box, as even the people who program them often have little to no idea how they make decisions. It’s not as critical when it’s just a picture of a cute puppy or a kitten. But it becomes important when an AI tries to interpret, say, a sequence of weather images that show…

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