AI

wipro-recruitment

Wipro Gives 10% Salary Hike, on a hiring spree In 2021 For New Skills

Wipro has revealed that the company has huge plans for future hiring for the Indian IT services provider. The company’s board has also approved a share buyback worth Rs. 9,500 crore. Wipro Has Robust Hiring Plans For The Second Half Of FY; To Hire Candidates With These Skills. Wipro has revealed that the leading IT services company in India has “robust” hiring plans for the upcoming second half of the financial year.

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The company is planning to get onboard freshers and laterals during the third and fourth quarters as well. While he didn’t specify the magnitude of hiring, he did say that the hiring will be across the US, Europe, and India. The company will be looking for candidates skilled in new-age technologies like artificial intelligence (AI), digital, and the internet of things (IoT).

Advanced AI: Deep Reinforcement Learning

Quite recently, Wipro had announced that employees who deliver high quality performance will be awarded with promotions in December. Promotions for the high performers will be handed out in bands up to B3. Employees in bands up to B3 account for about 80% of the company’s workforce. As the total employee strength in Wipro is more than 1,80,000, and 80% of this means 1,45,000 employees of Wipro.

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Wipro To Buyback Shares Worth Rs. 9500 Crores

Wipro’s board has also given the green signal to approve the share buyback worth Rs. 9500 crores as a part of the September quarter results on Tuesday. As much as 237.5 million equity shares or 4.16 per cent of the total paid-up capital will be bought by the Bengaluru based Wipro. As per reports, this buyback will be made from the existing shareholders under the tender-offer route on a proportionate basis. This was revealed from an exchange filing. Also, the price of the repurchase urchase has been fixed as Rs 400 per share and it is at a 6.25 per cent premium to Tuesday’s close.

Explore Wipro Careers here

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The Responsible AI for Social Empowerment (RAISE 2020) virtual summit

RAISE 2020 (Responsible AI for Social Empowerment) Artificial Intelligence Summit: Key Facts

 

Advanced AI: Deep Reinforcement Learning

PM Modi to inaugurate the Global Virtual Summit on Artificial Intelligence on October 5, 2020. The summit is organized by the Government of India in partnership with academia and industry. The summit aims to transform education, health, and agricultural areas.

In the history of human civilization, Artificial Intelligence is considered to be the next giant technological leap similar to electricity and the internet. With AI possessing the power to radically transform the economic and social fabric of the world we live in, it’s time to ask, how can we use AI responsibly for the good of humanity and for inclusive socio-economic development? The Responsible AI for Social Empowerment (RAISE 2020) virtual summit will be a Global Artificial Intelligence summit

RAISE is Responsible AI for Social Empowerment, 2020.

Highlights of the Summit: In June 2020, India joined the Global Partnership on Artificial Intelligence along with US, Australia, UK, France, Germany, and Canada.
Global Partnership on Artificial Intelligence: India is a founding member of GPAI. It supports human centric and responsible development and use of AI. In June 2020, the initiative was hosted by OECD (Organization for Economic Cooperation and Development) in Paris.

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The initiative will bridge the gap between theory and practice of Artificial Intelligence. This is to be done by supporting research and applied activities related to AI. The GPAI will bring together international organizations and partners from civil societies, academia and society to promote responsible evolution of AI.

Artificial Intelligence: AI is a branch of Computer Science that is concerned in making computers behave like humans. The technology provides ability to the machines to perform tasks such as perceiving, thinking, learning and problem solving.

Past
In June 2020, India joined the Global Partnership on Artificial Intelligence along with US, Australia, UK, France, Germany, and Canada.

Key Features of the Summit

The summit is held to exchange ideas of Artificial Intelligence for inclusion, social empowerment, transformation in key areas such as agriculture, health care, education, and smart mobility.
It calls for global participation in government representatives, academia, and opinion-makers.
The summit aims to encourage discussion on public infrastructure, transform society and build responsible Artificial Intelligence for social empowerment.
More than 38,700 stakeholders have registered for the summit from 125 countries
The summit will add 957 billion USD to the Indian economy by 2035.
The summit will discuss on education and awareness for responsible AI impact of data and AI in smart cities, leveraging AI for pandemic preparedness, role of data governance in enabling AI, building a future-ready Agricultural Supply Chain, and the role of data for responsible AI.
Global Partnership on Artificial Intelligence
India is a founding member of GPAI. It supports human-centric and responsible development and use of AI. In June 2020, the initiative was hosted by OECD (Organization for Economic Cooperation and Development) in Paris.

Alexa-course

The initiative will bridge the gap between theory and practice of Artificial Intelligence. This is to be done by supporting research and applied activities related to AI. The GPAI will bring together international organizations and partners from civil societies, academia, and society to promote the responsible evolution of AI.

About Artificial Intelligence Course

This course will introduce you to the potential of machine learning and help you reflect on how you can use it responsibly to enhance your journalism. Machine learning (ML) already powers many products we use every day. However, it is not always apparent to us that ML is behind them.

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Artificial intelligence New Algorithm replaces Writers, Journalists, and Poets

PT-3 Creative Fiction

Creative writing by OpenAI’s GPT-3 model, demonstrating poetry, dialogue, puns, literary parodies, and storytelling. Plus advice on effective GPT-3 prompt programming & avoiding common errors.

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The latest and greatest neural network for unrestricted natural language generation is OpenAI’s GPT-3. GPT-3 is like GPT-1 and the GPT-2 I’ve used extensively before1—only much more so, and then going beyond them in a fascinating new way.

GPT-3’s samples are not just close to human level: they are creative, witty, deep, meta, and often beautiful. They demonstrate an ability to handle abstractions, like style parodies.

Scaling works: quantity is a quality all its own.The scaling of GPT-2-1.5b by 116× to GPT-3-175b has worked surprisingly well and unlocked remarkable flexibility in the form of meta-learning, where GPT-3 can infer new patterns or tasks and follow instructions purely from text fed into it. What can we do with GPT-3? Here, we’re all about having fun while probing GPT-3’s abilities for creative writing tasks, primarily (but far from limited to) poetry. Fortunately, OpenAI granted me access to their Beta API service which provides a hosted GPT-3 model, letting me spend a great deal of time interacting with GPT-3 and writing things. Naturally, I’d like to write poetry with it: but GPT-3 is too big to finetune like I did GPT-2, and OA doesn’t (yet) support any kind of training through their API. Must we content ourselves with mediocre generic poetry, at best, deprived of finetuning directly on chosen poetry corpuses or authors we might like to parody? How much does GPT-3 improve and what can it do?

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Turns out: a lot! Below, I walk through first impressions of using GPT-3, and countless samples. In the latest twist on Moravec’s paradox, GPT-3 still struggles with commonsense reasoning & factual knowledge of the sort a human finds effortless after childhood, but handles well things like satire & fiction writing & poetry, which we humans find so difficult & impressive even as adults. In addition to the Cyberiad, I’d personally highlight the Navy Seal & Harry Potter parodies, the Devil’s Dictionary of Science/​Academia, “Uber Poem”, “The Universe Is a Glitch” poem (with AI-generated rock music version), & “Where the Sidewalk Ends”.

What BENCHMARK miss

The GPT-3 paper includes evaluation of zero-shot/few-shot performance across a wide range of tasks, but I fear that unless one is familiar with the (deadly dull) benchmarks in question, it won’t be impressive. You can skip to the appendix for more example like its poems, or browse the random samples.

The original OpenAI Beta API homepage includes many striking examples of GPT-3 capabilities ranging from chatbots to question-based Wikipedia search to legal discovery to homework grading to translation; I’d highlight AI Dungeon‘s Dragon model (example), and “Spreadsheets”/“Natural Language Shell”/“Code Completion”2. Andrew Mayne describes using GPT-3 to generate book recommendation lists & read interactive stories & engage in conversations with historical figures like Ada Lovelace3, summarize texts (such as for elementary school children, also available as a service now, Simplify.so) or summarize movies in emoji (Matrix: “🤖🤐”; Hunger Games: “🏹🥊🌽🏆”), convert screenplay ↔︎ story, summarize/​write emails, and rewrite HTML. Paras Chopra finds that GPT-3 knows enough Wikipedia & other URLs that the basic Q&A behavior can be augmented to include a ’source’ URL, and so one can make a knowledge base ‘search engine’ with clickable links for any assertion (ie. the user can type in “What year was Richard Dawkin’s The Selfish Gene published?” and GPT-3 will return a tuple like (“The Selfish Gene was published in 1976″,”https://en.wikipedia.org/wiki/The_Selfish_Gene”) which can be parsed & presented as a search engine). Hendrycks et al 2020 tests few-shot GPT-3 on common moral reasoning problems, and while it doesn’t do nearly as well as a finetuned ALBERT overall, interestingly, its performance degrades the least on the problems constructed to be hardest.

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Ryan North experimented with Crunchyroll anime, Star Trek: The Next Generation, & Seinfeld plot summaries. Max Woolf has a repo of GPT-3 example prompts & various completions such as the original GPT-2 “unicorn” article, Revenge of the Sith, Stack Overflow Python questions, and his own tweets (note that many samples are bad because the prompts & hyperparameters are often deliberately bad, eg the temperature=0 samples, to demonstrate the large effect of poorly-chosen settings as a warning). Janelle Shan experimented with weird dog descriptions to accompany deformed GAN-dog samples, and 10,000-year nuclear waste warnings based on the famous 1993 Sandia report on long-time nuclear waste warning messages for the Waste Isolation Pilot Plant. Summers-Stay tried imitating Neil Gaiman & Terry Pratchett short stories with excellent results. Arram Sabetti has done “songs, stories, press releases, guitar tabs, interviews, essays, and technical manuals”, with his Elon Musk Dr. Seuss poems a particular highlight. Paul Bellow (LitRPG) experiments with RPG backstory generation. Merzmensch Kosmopol enjoyed generating love letters written by a toaster. James Yu co-wrote a SF Singularity short story with GPT-3, featuring regular meta sidenotes where he & GPT-3 debate the story in-character. Daniel Bigham plays what he dubs “19 degrees of Kevin Bacon” which links Mongolia to (eventually) Kevin Bacon. Alexander Reben prompted for contemporary art/sculpture descriptions, and physically created some of the ones he liked best using a variety of mediums like matchsticks, toilet plungers, keys, collage, etc.

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Harley Turan found that, somehow, GPT-3 can associate plausible color hex codes with specific emoji. Even more perplexingly, Sharif Shameem discovered that GPT-3 could write JSX (a Javascript+CSS hybrid) according to a specification like “5 buttons, each with a random color and number between 1–10” or increase/​decrease a balance in React or a very simple to-do list and it would often work, or require relatively minor fixes. GPT-3 can also write some simple SVG shapes or SVG/Chart.js bar graphs, do text→LaTeX and SQL queries. While I don’t think programmers need worry about unemployment (NNs will be a complement until they are so good they are a substitute), the code demos are impressive in illustrating just how diverse the skills created by pretraining on the Internet can be. (Source: https://www.gwern.net/)