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How Having Bigger AI Models Can Have A Detrimental Impact On Environment

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The COVID crisis has skyrocketed the applications of artificial intelligence -- from tackling this global pandemic, to being a vital tool in managing various business processes. Despite its benefits, AI has always been scrutinised for its ethical concerns like existing biases and privacy issues. However, this technology also has some significant sustainability issues – it is known to consume a massive amount of energy, creating a negative impact on the environment. As AI technology is getting advanced in predicting weather, understanding human speech, enhancing banking payments, and revolutionising healthcare, the advanced models are not only required to be trained on large datasets, but also require massive computing power to improve its accuracy. Such heavy computing and processing consumes a tremendous amount of energy and emits carbon dioxide, which has become an environmental concern. According to a report, it has been estimated that the power required for training AI models emits approximately 626,000 pounds (284 tonnes) of carbon dioxide, which is comparatively five times the lifetime emissions of the average US car.


Artificial Intelligence Market Research Report (2020-2025) by Future Trend, Growth rate …

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Artificial intelligence uses the techniques such as natural language processing, machine learning, adaptive learning, deep learning, and computer vision …


Voice + AI Is Coming To The Workplace Loud And Clear

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Virtual assistants turn 16 this year and you don't have to look too hard – or speak too loudly – to find them. In fact, there will be around 8 billion voice-based devices by 2023 – more than the world's population today. From Amazon's Echo and Google's Assistant to Apple's Siri, Samsung's Bixby and Microsoft's Cortana, billions of people around the world are using their voices every day to schedule appointments, get directions, play music or get answers quickly-- all things that once required us to tediously type or write. Even Twitter recently announced that users can now audio tweet their inner musings. And yet, despite widespread adoption of voice-based devices in our personal lives, applications based on voice are nowhere as pervasive in our professional lives as they are in our homes.


Smart & Final Deploys Hypersonix's AI-Driven Analytics

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Smart & Final is rolling out Hypersonix's AI-driven analytics platform to support the company's enterprise analytics and digital transformation initiatives. The two companies started working together sixty days ago on a successful pilot program. With this announcement, Smart & Final officially joins a handful of early adopters in the grocery and consumer-commerce industries turning to the innovative company to help navigate the post-COVID-19 market. "Hypersonix is a key ingredient in leveraging actionable analytics that can be operationalized by our business teams as part of our on-going digital transformation," said Ed Wong, EVP and Chief Digital Officer at Smart & Final. "We established a great innovation-centric collaboration with Hypersonix where we are finding new ways to address our needs in key strategic areas for our business."


Roadmap to Natural Language Processing (NLP)

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Natural Language Processing (NLP) is the area of research in Artificial Intelligence focused on processing and using Text and Speech data to create smart machines and create insights. One of nowadays most interesting NLP application is creating machines able to discuss with humans about complex topics. IBM Project Debater represents so far one of the most successful approaches in this area. All of these preprocessing techniques can be easily applied to different types of texts using standard Python NLP libraries such as NLTK and Spacy. Additionally, in order to extrapolate the language syntax and structure of our text, we can make use of techniques such as Parts of Speech (POS) Tagging and Shallow Parsing (Figure 1).


Global Big Data Conference

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Artificial intelligence is beginning to be usefully deployed in almost every industry from customer call centers and finance to drug research. Yet the field is also plagued by relentless hype, opaque jargon and esoteric technology making it difficult for outsiders identify the most interesting companies. To cut through the spin, Forbes partnered with venture firms Sequoia Capital and Meritech Capital to create our second annual AI 50, a list of private, U.S.-based companies that are using artificial intelligence in meaningful business-oriented ways. To be included, companies had to be privately-held and focused on techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see"). The list was compiled through a submission process open to any AI company in the U.S. The application asked companies to provide details on their technology, business model, customers and financials like funding, valuation and revenue history (companies had the option to submit information confidentially, to encourage greater transparency).


Introduction to Word Embedding

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Humans have always excelled at understanding languages. It is easy for humans to understand the relationship between words but for computers, this task may not be simple. For example, we humans understand the words like king and queen, man and woman, tiger and tigress have a certain type of relation between them but how can a computer figure this out? Word embeddings are basically a form of word representation that bridges the human understanding of language to that of a machine. They have learned representations of text in an n-dimensional space where words that have the same meaning have a similar representation.


Three Ways Artificial Intelligence Is Changing Medicine

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We may not be at the point where you overhear your surgeon saying, "Hey, Google, pass the scalpel," but artificial intelligence (AI) is gradually making its way into the healthcare industry and, by extension, dermatology and plastic surgery practices. Even in its limited use, AI is already helping providers offer their patients better care, whether it's preop, in the OR or during the recovery process. Your experience with a medical practice starts as soon as you look for information online. You might have questions for the practitioner or want to book an appointment. In the past, you would have emailed or called the practice, but you may now find yourself speaking to an AI assistant on the practice's website.


AI startup Spiketrap secured $3 Million in Seed Funding

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Spiketrap, a California based AI-powered consumer intelligence platform, has now secured $3 million in a seed funding round. Spiketrap is founded by the Kieran Fitzpatrick. It provides an AI-powered platform that enables companies and brands to understand conversations at scale in a real-time scenario. The company helps customers in deriving insights faster and providing rich data for data-driven decision making. The company comprises a team of more than 15 people from industry leaders which includes Logitech, Apple, Amazon, and AdColony.


Artificial Intelligence In Wealth Management To Provide Hybrid Services

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Artificial Intelligence (AI) refers to intelligent machines that work and react like humans. AI helps to deliver insights to complex client questions in real time through its virtual conversational interface between business and clients. AI enabled applications such as natural language generation (NLG) is closing the gap between data analysis and investment decisions, providing real-time insights through automated trading strategies. For instance, according to a survey in 2018 by Forbes, 34% of wealth management companies have currently deployed AI within their firms and around 99% plan on deploying AI within the next 3 years. Companies such as Wells Fargo and Bank of America have already deployed AI services to better serve clients.