"The field of Machine Learning seeks to answer these questions: How can we build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes?"
– from The Discipline of Machine Learning by Tom Mitchell. CMU-ML-06-108, 2006.
In machine learning terminology, the sum of squared error is called the "cost". This equation is therefore roughly "sum of squared errors" as it computes the sum of predicted value minus actual value squared. The 1/2mis to "average" the squared error over the number of data points so that the number of data points doesn't affect the function. See this explanation for why we divide by 2. In gradient descent, the goal is to minimize the cost function. We do this by trying different values of slope and intercept.
If you're worried about facial recognition firms or stalkers mining your online photos, a new tool called Anonymizer could help you escape their clutches. The app was created by Generated Media, a startup that provides AI-generated pictures to customers ranging from video game developers creating new characters to journalists protecting the identities of sources. The company says it built Anonymizer as "a useful way to showcase the utility of synthetic media." The system was trained on tens of thousands of photos taken in the Generated Media studio. The pictures are fed to generative adversarial networks (GANs), which create new images by pitting two neural networks against each other: a generator that creates new samples and a discriminator that examines whether they look real. The process creates a feedback loop that eventually produces lifelike profile photos.
Machine learning can be deployed virtually anywhere there's data. You've likely worked with tools like Google Analytics, Typeform, Hubspot, and others. In fact, machine learning can be used to make all of these tools more powerful, whether it's predicting traffic and conversions, predicting any data in a Typeform, or even driving growth hacking. Nowadays, AutoML tools seem to be taking over the world. If you Google "AI without code," you'll find tools like RunwayML for creative applications and Obviously.AI for tabular data, besides the more well-known Google AutoML tools (though, to be fair, Google's version is fairly hard to use).
There has been considerable recent progress in protein structure prediction using deep neural networks to infer distance constraints from amino acid residue co-evolution1–3. We investigated whether the information captured by such networks is sufficiently rich to generate new folded proteins with sequences unrelated to those of the naturally occuring proteins used in training the models. We generated random amino acid sequences, and input them into the trRosetta structure prediction network to predict starting distance maps, which as expected are quite featureless. We then carried out Monte Carlo sampling in amino acid sequence space, optimizing the contrast (KL-divergence) between the distance distributions predicted by the network and the background distribution. Optimization from different random starting points resulted in a wide range of proteins with diverse sequences and all alpha, all beta sheet, and mixed alpha-beta structures.
Sian Williams, Audience Strategy and Planning Director at MediaCom North, explains how AI offers a future of increased automation, faster decision-making and'hyper-personalisation' that will make marketing comms more effective and businesses more efficient. Robots are science fact not fiction, machines may well inherit the earth, and artificial intelligence can actually enhance the way we engage with human intelligence. As more interactions become digitised, the data landscape is only getting bigger and AI, and within it machine learning, will increasingly fuel that growth. The two terms are often used inter-changeably but whilst AI creates the structure of computational human intelligence it is machine learning that, sans specific programming, delivers on how quickly and effectively data will be processed and decisioned against. If AI is the brain itself, full of raw potential, then machine learning is at least one of the'cortexes' able to process information and develop intelligence and skill by using one'experience' to inform another.
When you hear the term "AI," many people would think that this is a super robot that is going to destroy the world. Although this is a part of AI, that isn't what AI is. Artificial Intelligence is intelligence demonstrated by machines, which is the opposite of our intelligence, Natural Intelligence. How were we able to create an intelligence inside of code? The answer is pretty simple.
In my first article on Time Series, I hope to introduce the basic ideas and definitions required to understand basic Time Series analysis. We will start with the essential and key mathematical definitions, which are required to implement more advanced models. The information will be introduced in a similar manner as it was in a McGill graduate course on the subject, and following the style of the textbook by Brockwell and Davis. A'Time Series' is a collection of observations indexed by time. The observations each occur at some time t, where t belongs to the set of allowed times, T. Note: T can be discrete in which case we have a discrete time series, or it could be continuous in the case of continuous time series.
Artificial intelligence technologies are being used across industries to automate and improve the efficacy of different activities. The advanced machine learning systems are equipped to replicate the discreet thinking and analysis patterns demonstrated by humans. This allows companies to leverage AI in performing some of the complex cognitive tasks with minimal human intervention. While AI can be applied to varied use-cases, social media is one segment where it has become a major catalyst for companies to grow. For example, AI chatbots for business are helping companies to stay connected with their audience.
COVID-19 virus hit us hard. Warnings from Nicolas Taleb that our interconnectedness could cause wide pandemic were true. Schools are closed and most of us are working from home, spending time in isolation and trying not to spread the virus. At the moment when I am writing this, all the borders in my home country are closed, all bars and malls are closed and you can not go out after 5 PM. Apart from that, this pandemic has a huge impact on the economy.
Researchers at Google have developed a new AI tool called Chimera Painter that turns doodles into unusual creatures. This tool uses machine learning to create representation based on the user's rough sketches. Before this, Nvidia has used a similar concept with landscapes, and MIT and IBM have produced a similar idea with buildings. A high level of technical knowledge and artistic creativity is required to create art for digital video games. Game artists need to promptly iterate on ideas and develop many assets to meet tight deadlines.