AI News, AI Business Transformation Playbook for Executives artificial intelligence

Human + Machine: Reimagining Work in the Age of AI - H. James Wilson

Daugherty show that the essence of the AI paradigm shift is the transformation of all business processes within an organization–whether related to breakthrough innovation, everyday customer service, or personal productivity habits.

As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly—or to completely reimagine them.

experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results.

Andrew Ng

born 1976) is a Chinese-American computer scientist known as one of the most prolific researchers in machine learning and AI, with his work helping incite the recent revolution in deep learning.[2]

Also a business executive and investor in the Silicon Valley, Ng co-founded and led Google Brain and was a former Vice President and Chief Scientist at Baidu, building the company's Artificial Intelligence Group into a team of several thousand people.[3]

Since 2018 he launched and currently heads AI Fund, initially a $175-million investment fund for backing artificial intelligence startups.

In 1997, he earned his undergraduate degree with a triple major in computer science, statistics, and economics at the top of his class from Carnegie Mellon University in Pittsburgh, Pennsylvania.

At MIT he built the first publicly available, automatically-indexed web-search engine for research papers on the web (it was a precursor to CiteSeer/ResearchIndex, but specialized in machine learning).[6]

He became Director of the Stanford Artificial Intelligence Lab, where he taught students and undertook research related to data mining, big data, and machine learning.

His machine learning course CS229 at Stanford is one of the most popular courses offered on campus with over 1000 students enrolling some years.[11][12]

Since joining Stanford in 2002, he has advised dozens of Ph.D and M.Sc students, including Ian Goodfellow, Quoc Le and many other students who have gone on to work for academia or companies like Google, Facebook, Apple, Twitter, and 23andme.[6]

The rationale was that an efficient computation infrastructure could speed up statistical model training by orders of magnitude, ameliorating some of the scaling issues associated with big data.

Ng researches primarily in machine learning, deep learning, machine perception, computer vision, and natural language processing;

In 2011, Ng founded the Google Brain project at Google, which developed large scale artificial neural networks using Google's distributed computer infrastructure.[24]

Among its notable results was a neural network trained using deep learning algorithms on 16,000 CPU cores, which learned to recognize cats after watching only YouTube videos, and without ever having been told what a 'cat' is.[25][26]

Within Stanford, they include Daphne Koller with her 'blended learning experiences' and co-designing a peer-grading system, John Mitchell (Courseware, a Learning Management System), Dan Boneh (using machine learning to sync videos, later teaching cryptography on Coursera), Bernd Girod (ClassX), and others.

It offered a similar experience to MIT's Open Courseware except it aimed at providing a more 'complete course' experience, equipped with lectures, course materials, problems and solutions, etc.

Widom, Ng, and others were ardent advocates of Khan-styled tablet recordings, and between 2009–2011, several hundred hours of lecture videos recorded by Stanford instructors were recorded and uploaded.

The course featured quizzes and graded programming assignments and became one of the first and most successful Massive open online courses (MOOCs) created by a Stanford professor.[33]

One of the students (Frank Chen) claims another one (Jiquan Ngiam) frequently stranded him in the Stanford building and refused to give him a ride back to his dorm until very late at night, so that he no choice but to stick around and keep working.

This is a non-technical course designed to help people understand AI's impact on society and its benefits and costs for companies, as well as how they can navigate through this technological revolution.[36]

Ng has filed patents in sundry things from text-to-speech (TTS) systems, compressed video and audio recordings, rechargable batteries, electronic roll towel dispensers, an energy saving cooker, and a one-size-fits-all T-shirt.[47]

Ng is one of the scientists credited with bringing humanity to AI, and he sees AI as a technology that will improve the lives of people, not an anathema that will 'enslave' the human race.[3]

In 2017, Ng said he supported basic income to provide people tools to learn about AI and spend time studying so that they can re-enter the workforce as productive members.

MIT Sloan Executive Education innovation@work Blog

While the course isn’t necessarily targeted towards dgital tansformation agencies in particular, it’s easy to glean valuable insight into the future of business strategy as a whole from the content.

Much of what’s been written in the popular press and on social media centers around big, scary questions, such as: Jokes aside, these questions are based largely (though not completely) on runaway imaginations and jumping to conclusions about what the future will hold for these emerging technologies.

From AndPlus’ definition, digital transformation involves “organizational change through the use of digital technologies and business models to improve performance.” Under this definition, the three pillars of digital transformation are: Understood this way, digital transformation is more than simply taking existing non-digital business processes (perhaps paper-based or manual) and creating electronic equivalents of them.

In each of the preceding examples, the value that AI brings to the table isn’t that AI is “smarter” than humans—it’s not, now, and may never be considered “smarter.” AI’s value to a business rather lies in these benefits: The drawback is that there is no “general purpose” AI system—if you want to apply AI to some task, you have to teach it that task, using huge quantities of data.

Teaching an AI system to distinguish defective parts in photographs, for example, means “training” it with tens of thousands of photos (each of which must be tagged as “has defects” or “defect-free” by humans) of the part in question.

AI’s Place in a Digital Transformation Strategy Back in 1985, Harvard Business School professor Michael Porter identified three generic strategies that businesses use to attain competitive advantage: Cost leadership (minimizing the costs of providing goods and services), differentiation (distinguishing oneself positively from one’s competitors), and focus (concentrating on particular, narrow market segments).

Old-style business organization, management, planning, and execution are no longer viable, and companies that insist on adhering to old approaches risk being left in the dust by their faster, more nimble competitors.

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