If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Digital generated image of data. Lemonade is one of this year's hottest IPOs and a key reason for this is the company's heavy investments in AI (Artificial Intelligence). The company has used this technology to develop bots to handle the purchase of policies and the managing of claims. Then how does a company like this create AI models? Well, as should be no surprise, it is complex and susceptible to failure.
In this free issue: current machine learning deep learning trends, news, resources, sneak preview of paid subscriber content. Having a searchable blog that requires authentication allows us to show every one what kind of resources are available. Free signups get previews and paid subscribers can quickly access and search for relevant resources. We also link to our Medium blog networks this way we have all the information in one place, organized by topics and keywords. Current easter eggs We routinely send easter eggs to paid subscribers.
'The machines are taking over' has become a long drawn concept and a proverb now. To cite some examples following the herd would be Amazon, DHL, CIG, Siemens, Uber, and Tesla. This doesn't come off as a surprise when it has already been established that automation has fruitful results in the long term. Canon India seems to walk the same path, and have really robust plans for the future, relying on automation. Express Computer's Gairika Mitra gets into an invigorating chat with K Bhaskhar, Senior Vice President, Business Imaging Solutions (BIS), Canon India, to gain further clarity on this.
Transformers and pre-trained models can be considered one of the most important developments in the recent years of deep learning. Beyond the research breakthroughts, Transformers have redefined the natural language understanding(NLU) space sparking a race between lead AI vendors to build bigger and more efficient neural networks. The Transformer architecture has been behind famous models such as Google's BERT, Facebook's RoBERTa or OpenAI's GPT-3. Is not surprising that many people believe that only big companies have the resources to tackle the implementation of Transformer models. Earlier this year, the deep learning community was astonished when Microsoft Research unveiled the Turing Natural Language Generation (T-NLG) model which, at the time, was considered the largest natural language processing(NLP) model in the history of artificial intelligence(AI) with 17 billion parameters.
As the world prepares to embrace the new normalcy of life, a lot of companies have started allowing their employees to work from home to ensure their safety after the outbreak of COVID-19. This is especially true for organizations with computer programming, data science, artificial intelligence, engineering, and machine learning workforce. Implemented as a temporary solution, remote work is likely to become the normal way of keeping such businesses functional. Most of the companies have always preferred hiring locally, requiring employees to stay in the local region even when allowing work from home. Due to this, individuals from different parts of the world migrate to locations that have more job opportunities such as Silicon Valley, New York City, Seattle, etc.
The story of quantum computing hardware companies is well known. But as tech giants Amazon and Microsoft push the quantum computing conversation to the cloud, we're also seeing quantum computing software companies emerge. One such company, Zapata, is building an enterprise software platform for quantum computing. Businesses with deep pockets are increasingly exploring quantum computing, which depends on qubits to perform computations that would be much more difficult, or simply not feasible, on classical computers. Quantum advantage, the inflection point when quantum computers begin to solve useful problems, is a long way off (if it can even be achieved) but its potential is massive.
Machine Learning Pipelines with Azure ML Studio What can Azure ML pipelines do? In this project-based course, you are going to build an end-to-end machine learning pipeline in Azure ML Studio, all without writing a single line of code! This course uses the Adult Income Census data set to train a model to predict an individual's income. It predicts whether an individual's annual income is greater than or less than $50,000. The estimator used in this project is a Two-Class Boosted Decision Tree classifier.