As COVID-19 continues to spread, we are acutely aware of the impact this is having on families, businesses, and communities. This is a global health
Neural networks can perform well on tasks such as image classification, language translation, and game playing. However, they usually fail to perform well in tasks
Time series models predominantly, over the years, have focussed on individual time series via local models. This changed with the popularisation of deep learning techniques.
A key balancing act in machine learning is choosing an appropriate level of model complexity: if the model is too complex, it will fit the
Games like chess, GO, and Atari have become testbeds of testing deep reinforcement learning algorithms. Companies like DeepMind and OpenAI have done a tremendous amount
It is humbling to think of the number of tools, languages, techniques and applications a machine learning ecosystem has nurtured. Choosing the best fit out
Batch normalisation (batch norm) is one of the most widely used deep learning techniques to stabilise and accelerate training in deep neural networks. This technique
Regardless of what is happening around the world, the AI community are one productive bunch, and they have something interesting to share almost every day.
There is a growing interest in expanding the scope of edge ML to microcontroller-class devices. And, this is where TinyML comes into the picture. As
The White House, today, in their official press release has announced the release of COVID-19 Open Research Dataset(CORD-19). This dataset was released with the combined
Ever since the COVID-19 outbreak, the disease has claimed the lives of more than 7,000 people, infecting over 183,000, and prompting a wave of travel
Data is the new oil is the sayings of the past. Data is my property, and I should get paid for it might be the
Building high-quality simulators for physical phenomena require exceptional engineering efforts combined with expensive computational resources. This reason alone barricades many kinds of research. Even if
Visual speech recognition (also known as lipreading) is considered to be one of the most futuristic applications of AI. So far, there haven’t been major
Every technological advancement has benefitted hugely from the communities that have been formed around it. Communities nurture developers and evangelists in a way that strengthens
When OpenAI released its GPT model, it had 1.5 billion parameters and made it the biggest model back then. It was soon eclipsed by NVIDIA’s
AI is one of the most happening domains in the world right now. It would take a lifetime to skim through all the machine learning
Any company that releases a brand new car has to wait at least for the first-quarter sales to come in before deciding on the future
Any machine learning solution comes with two primary challenges — accuracy and training time. There is always a trade-off between these two. There are places
The ability of natural language in machines, so far, has been elusive. However, the last couple of years, at least since the advent of Google’s
Image classification tasks occupy the majority of machine learning experiments. Their critical usage in medical diagnosis, digital photography, self-driving cars and many others have attracted
Over the last seven days, online media moguls Facebook, YouTube and Twitter have been in the news for stifling the content on their platforms. While
As COVID-19 reaches more than 60 countries with global cases topping 95,500 and the number of death tolls crossing 3,000, the whole world is doing
Behind every successful scientific implementation, there is a theory that supports the results or allows one to anticipate the consequences. In the case of machine
Does democratisation of machine learning work for everyone or is there a flip side to it? What do the developers with no machine learning background
The age of algorithmic innovations has now entered a new realm where the researchers are finding flaws in the techniques through adversarial attacks. In the
There are close to 3.5 billion smartphone users in the world, and if you happen to be one of them, then the chances are high
The popularity of compression techniques grew with the increasing sizes of machine learning models, which grew in order to cater to the growing number of
Physicists from Ghent University in collaboration with AI researchers from Ontario, Canada, have successfully demonstrated with their new generative model (RUGAN), how to produce snapshots
The role of machine learning and its forecast of societal impacts have been oscillating between future haven of benevolent possibilities and exaggerated dystopia. The ethics
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