Mediaboss Marketing

How can culinary traditions be preserved, Spratt asked, when food is ultimately meant to be consumed? UNESCO recognizes French cuisine as an intangible heritage, which it defines as not the cultural manifestation itself, but rather the wealth of knowledge and skills that is transmitted through it from one generation to the next.

The gastronomic algorithms project, in contrast, emphasizes the cultural manifestation itself. Specifically, the project focuses on the artistic dimension of plating through Passards use of collages to visually conceive of actual plates of food. Taking this one step further, the project also explores how fruit-and-vegetable-embellished paintings by the Italian Renaissance artist Giuseppe Arcimboldo (1526-1593) could be reproduced through the use of artificial intelligence tools.

Spratt then asked the leading question of her research: How could GANs, a generative form of AI, emulate the culinary images, and would doing so visually reveal anything about the creative process between the chefs abstracted notions of the plates and collages, and their actual visual execution as dishes?

Experimenting With Datasets

Although Passards collages are a source of inspiration for his platings, a one-to-one visual correlation between the appearance of both does not exist. The dataset initially comprised photos posted by Passard on Instagram, images provided by the restaurants employees, and photos captured by Spratt at L'Arpge during each of the different seasons. This was later supplemented by images of vegetables and fruits on plates, as well as sliced variations procured from the internet using web scraping tools.

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Artificial Intelligence and the Art of Culinary Presentation - Columbia University

Artificial intelligence is set to be the future of humanity and the next step of our evolution. Scientists and analysts believe that with this type of technology, we would be able to become multi-planetary species in the future and continue to conquer the Milky Way.

Even though the concept of AI is still in its early stages of development, some industries have managed to integrate it and use it as a key tool in their everyday operations. With that being said, we wanted to take a look at some industries and sectors that have managed to incorporate this type of technology and make the best use of it. Lets check them out.

Gaming Sites

Online gaming has become extremely popular in the past 5-6 years. Online casinos are now accessed by millions of players who are in search of unique gaming experience, excitement and fun. These sites are expected to rule the gambling industry in the next couple of years due to the great features that they have.

There are two types of AI that they use, and to explain them in the best way possible, well use NetBet, a reputable platform that offers players the chance to both play casino games and bet on sports. When it comes to playing casino games, this platform uses AI software called RNG. Random Number Generators create random outcomes of the games, thus giving each player an equal chance of winning.

The second type of AI covers both the sports betting online section and the gambling section. This AI software is called SSL-encryption technology and it protects the players by taking all of their data and turning it into an unbreakable code. The SSL-encryption security system makes it impossible for third parties to gain access to sensitive data. In doing so, players can bet on the games and play casino games without having to worry about anything.

Automotive Industry

The automotive industry is progressing at a really fast pace. Futuristic concept cars are already in their trial versions and every manufacturer is on a quest to bring the future of cars right now. If you are asking how AI is used in this sector, well take two companies as an example, as they both have implemented the same AI for their products.

The first example is Tesla. Ever since this car company entered the market, it has been creating futuristic electric vehicles that are believed to be the future of cars. They have great endurance, fantastic performance, and most recently they use AI in the form of self-driving mode. Autopilot mode in cars is set to be the future of the automotive industry. The second example that we wanted to mention is Waymo. This company is already exploring advanced technologies on self-drive mode on the streets of Phoenix.

Medical Sector

The medical sector is one of the sectors in which artificial intelligence would literally revolutionize. With advanced AI in this industry, it would be much easier to develop drugs that can cure some of the worlds current unbeatable diseases. STDs are a good example of that. Advanced AI in the medical sector would help in patient care and monitoring, developing specific drugs, diagnosis, treatment protocol development, and personalized medicine.

The good thing about AI in medicine/healthcare is that some companies already use basic forms of AI to power their networks. The Mayo Clinic and the British National Health Service are the two most popular and most well-known examples.

Conclusion

While many people oppose AI and believe that the technology will ruin our lives by replacing the human workforce and increasing the unemployment rate, it is a fact that there are some tasks that these robots would complete in a much more efficient and effective way. As time goes by, it is becoming clearer that this technology will represent our future.

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Artificial Intelligence in the World Today - Prescott eNews

Do you have proven expertise in Artificial Intelligence and Machine Learning and an established international reputation within the field, both in industry and academia? Are you looking for a challenging role in an environment that is open, vibrant and welcomes new ideas? Then Be The Change, follow your passion and join the University of East London as Professor of Artificial intelligence and Machine Learning.

These are exciting times at the University as, under a brand new transformational 10-year strategy, Vision 2028, were committed to providing students with the skills necessary to thrive in an ever-changing world, includingincreasing the diversity of the talent pipeline, particularly for Industry 4.0 jobs. Our pioneering and forward-thinking vision is set to make a positive and significant impact to the communities we serve too, and inspire our staff and students to reach their full potential. This is your chance to be part of that journey.

Join us, and youll be a key member of our Computer Science & Digital Technologies departments School of Architecture, Computing and Engineering team. Your challenge? To raise the profile of the department and school, specifically in impactful applied research in disciplines that include Deep Learning, Computer Vision and Natural Language Processing. But thats not all. Well also rely on you to lead and develop the Schools work, both in relation to taught courses and in terms of research, consultancy, knowledge transfer and income generation. And, as a senior academic leader, youll be instrumental in shaping the Schools strategy for promoting research, learning & teaching and employability initiatives.

Playing a prominent role in obtaining funding for research and knowledge exchange activities in your area of expertise will be important too. Well also encourage you to contribute to other aspects of the Schools work too, such as staff development activities, mentoring and supporting the development of early career researchers and joint supervision of PhD students. Put simply, youll bring leadership, vision and inspiration for the future direction of research and teaching in AI.

To succeed, youll need a PhD in Computer Science or other relevant area and experience of teaching in higher education or training in a professional context and applying innovative and successful approaches to learning. Youll also need a proven ability to lead on the fusion of practice and theory in specific disciplines, in-depth experience of research & knowledge exchange projects and a record of significant research & knowledge exchange grant capture and/or income generation or equivalent. As comfortable developing and managing major research grant applications as you are communicating academic findings to policy and wider public audiences, you also have experience of PhD supervision as a Director of Studies and other research mentorship activities.

In summary, you have what it takes to act as a role model and ambassador to raise the Universitys profile and increasing its impact and influence and establish links with a variety of businesses, public and third sector organisations.

So, if you have what we are looking for and are keen to take on this exciting challenge, get in touch.

At the University of East London, we aim to attract and retain the best possible staff and offer a working environment at the heart of a dynamic region with excellent transport links. You can look forward to a warm, sincere welcome, genuine camaraderie and mobility in an institution led with passion, visibility and purpose. Your impact, resilience and sense of collegiality will directly contribute to the Universitys future and those of the students whose lives you will touch and change forever. We also offer a great range of benefits including pension, family friendly policies and an on-site nursery and gym at our Docklands Campus.

Closing date: 13 April 2021.

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Professor of Artificial intelligence and Machine Learning job with UNIVERSITY OF EAST LONDON | 249199 - Times Higher Education (THE)

AI governance touches many functional areas within the enterprise data privacy, algorithm bias, compliance, ethics, and much more. As a result, addressing governance of the use of artificial intelligence technologies requires action on many levels.

It does not start at the IT level or the project level, says Kamlesh Mhashilkar, head of the data and analytics practice at Tata Consultancy Services. AI governance also happens at the government level, at the board of directors level, and at the CSO level, he says.

In healthcare, for example, AI models must pass stringent audits and inspections, he says. Many other industries also have applicable regulations. And at the board level, its about economic behaviors, Mhashilkar says. What kinds of risks do you embrace when you introduce AI?

As for the C-suite, AI agendas are purpose-driven. For example, the CFO will be attuned to shareholder value and profitability. CIOs and chief data officers are also key stakeholders, as are marketing and compliance chiefs. And thats not to mention customers and suppliers.

Not all companies will need to take action on all fronts in building out an AI governance strategy. Smaller companies in particular may have little influence on what big vendors or regulatory groups do. Still, all companies are or will soon be using artificial intelligence and related technologies, even if they are simply embedded in the third-party tools and services they use.

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AI governance: Reducing risk while reaping rewards - CIO

Artificial intelligence is not old news. According to Stanfords 2021 AI Index, the global corporate AI investment is at a record high of $67 billion. PWCs 22nd Global CEO Survey shows that 77% of Fortune 500 CEOs are planning to or have already started AI initiatives. With the increasing importance of artificial intelligence, all eyes are on data science to deliver substantial results.

The advantage that comes with artificial intelligence for businesses is common knowledge in the tech world. The 2020 McKinsey Global AI Survey states that AI is contributing more than 20% of EBIT (Earnings Before Interest and Tax) for an elite group of artificial intelligence practitioners. Additionally, these companies have bigger budgets to spend on artificial intelligence initiatives than their competitors. With this comes the ability to develop AI solutions that they require in-house, instead of depending on external suppliers.

As data science advances, the pressure for the field to deliver tangible results and live up to its hype increases. A significant yet understated role for the success of artificial intelligence products in the AI Product Owner (AI PO). Heres everything you need to know about AI PO.

Scrum framework, a popular agile development method defines the role of a product owner as someone who is responsible for maximizing the value of the scrum team. The scrum framework depends on the role of a product owner, scrum master, and developer. By this, we understand that a product owner creates a product vision, communicates the vision with the stakeholders, and creates the product backlog. The Scrum framework also dictates that a PO is required to have a business, user experience, technical and communication skills.

An extended, specialized role of a product owner is the role of an AI PO. AI POs inherit the duties of a general PO with the difference that the AI POs work revolves around artificial intelligence-based products.

AI-powered products obviously differ from conventional software products. AI products use data to learn patterns without developer support. Unlike traditional software products, AI products improve on their own as and when the data keeps coming. Machine learning facilitates the building of products that were not possible to build before the emergence of AI like speech recognition devices, automating driving, etc. Because AI products hold such immense power, it is crucial for AI POs to adjust their skills to adapt themselves.

Firstly, all AI POs need to know everything about AI-based products, from how they work, their merits, and then pitfalls. Secondly, AI POs need to attentively monitor the predictions made by the AI models. Artificial intelligence is based on statistical assumptions, so their predictions need to be observed for uncertainty. AI POs should make it to a point to design AI applications to include human-decision making wherever necessary because one wrong prediction can have grave consequences. AI-based products are also dynamic. They identify how customers react to the prediction. This is how the system knows to make adjustments to data. Lastly, AI POs need to understand that AI development differs from software development and its workflow. While traditional software development can follow a modular and structural approach, AI developments test various hypotheses and perform quickly. Understanding that machine learning development isnt as gradual as traditional software development is important to communicate the expectations with stakeholders.

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Artificial Intelligence Product Owners Are The Key For Business Success - Analytics Insight