Mediaboss Marketing

The Role

Applications are invited for a PDRA post in Artificial Intelligence.

1. Work closely with multi-national consumer goods corporation to identify short-list of applications of Artificial Intelligence (AI) in data mining, image processing, knowledge gathering etc. and to identify a short-list of projects that would benefit from AI methods.

2. For projects on the short-list, to deeper dive into the projects in order to define deliverables, what data is needed, milestones, etc. Deliverables could include a finished working model, successful proof of principle and a clear path forward, or a detailed assessment of why the proof of principle was not successful together with recommendations on how to address the problem in the future.

3. Over the course of the project duration, to undertake at least three R&D projects at Durham and to present a monthly updates to the relevant project teams at the corporation.

4. To hold a final workshop session at the corporation summarising and presenting the R&D work.

Continued here:
Postdoctoral Research Associate in Artificial Intelligence job with DURHAM UNIVERSITY | 215559 - Times Higher Education (THE)

Artificial Intelligence has arrived and it is good time that the C-suite especially the CEOs take a note of it. However, with the media hype surrounding digital transformation and AI the decision-makers of an enterprise often left in quandary as to how and when to implement AI and what to do with this business transformative technology.

With tangible results and takeaways, AI has shown real outcomes for early adopters resulting in a sense of trust and a feeling of assurance. To aid the C-Suite to derive benefits from this technology, Harvard Business Review has come up with a set of pointers which enterprisers both big and small need to know, for AI success in their workplace-

1. C-suite must take its time to evaluate the critical success from AI before deciding on a pilot.

2. It is good to believe in the hype surrounding AI implementation, disruptive technologies can potentially boost enterprise returns.

3. AI transformation might not succeed without the support of decision-making management.

4. Partnering for capability and capacity creation is a must for AI success.

5. Trust other technologies too, and avoid the temptation of putting tech teams solely in charge of AI implementation.

6. Accelerate the enterprise AI journey with a portfolio approach.

7. Machine Learning is powerful, but weigh your enterprise use cases before selecting the technology.

8. Build digital capabilities before an AI pilot project.

9. Take the change in overseeing the AI pilot in the first place.

10. Beware, people, change management and process-up-gradation are the biggest challenges.

The buzz around Artificial Intelligence (AI) has grown by leaps and bounds, all set to instil confidence among the C-suite all across the world. This is marked by an increase in investments and the widespread interest by venture capitalists, tech powerheads and change-makers. AI-infused digital transformation success stories are becoming all the louder and more prominent across enterprises crisscrossing domain functionalities.

The key adoption point of the IA influx arises from the adoption in AI machine learning and NLP infusion, to deliver more output and results that suits all the AI adopters. The AI adaptability across different industries will be different from BFSI, Telecom and Logistics all set to lead the way, while healthcare and the government sector is slowly and steadily preparing for the transitional shift.

In the future, developing new business models to build a growth path that is flexible and robust will be critical to digitization. The same seems to hold for AI, early AI adopters have been very proactive and robust in adoption g to the change, setting up examples for others to follow.

Summing up, the C-Suite must not make any mistake, the digital adoption is here, and the faster they realize its presence and embrace to these new technologies, the quicker they would adopt and stay in the competition race, else the time will come soon for perish. We are talking of a technology-dominated digital transformation era in some years from now.

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Kamalika Some is an NCFM level 1 certified professional with previous professional stints at Axis Bank and ICICI Bank. An MBA (Finance) and PGP Analytics by Education, Kamalika is passionate to write about Analytics driving technological change.

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How do CEO's Succeed with Artificial Intelligence at their Workplace? - Analytics Insight

While there's plenty to be critical about when it comes to retiring U.S. Rep. Will Hurd his records on the environment and health care, for example it's a fair bet at least some of his constituents will miss his bipartisanship.

After all, the San Antonio-area Republican co-wonAlleghenyCollege's 2018Prize for Civility in Public Life for his 30-hour "bipartisan road trip" with Beto O'Rourke, back when when the latter was just another Texas congressman and not yet a Democratic superstar.

Apparently, even in the waning months of his term, Hurd has kept up that spirit of reaching across the aisle.

The former CIA intelligence officer recentlyworked with U.S. Rep. Robin Kelly, D-Illinois, to author a detailed report on how to keep the U.S. from falling behind China on artificial intelligence. That's important, the pair argue, because AI has big implications for defense and national security.

Among the two House members' suggestions: getting the federal government to devote more money to deploying safe AI and cutting off Chinas access to AI-specific microchips.

The techie bible Wired Magazine was impressed enough with the pair's work that it devoted some serious real estate to letting them delve into their plan. Turns out Hurd and Kelly are alsodrafting a congressional resolution on their AI concerns and plan to introduce similar legislation.

Some of that I hope we get done in this Congress, and others can be taken and run with in the next Congress, Hurd told the mag.

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San Antonio GOP Congressman Will Hurd Reaches Across the Aisle on Artificial Intelligence - San Antonio Current

SAN FRANCISCO, July 29, 2020 /PRNewswire/ -- The global artificial intelligence in diagnostics market size is expected to reach USD 3.0 billion by 2027, expanding at a CAGR of 32.3%, according to a new report by Grand View Research, Inc. Increase in the number of healthcare Artificial Intelligence (AI) diagnostic startups coupled with huge investments by venture capitalist firms to develop innovative technologies that allow fast and effective diagnostic procedures due to continuous increase in number of patients suffering from chronic diseases supports the growth of the market. Around 33.3% of all healthcare AI SaaS companies are engaged in developing diagnostics, making it largest focus area for startups in the market.

Growing investments and funding for AI in healthcare is also one of the key factors driving the market. For instance, in 2016, the U.S.-based startup, PathAI, secured USD 75.2 million investment for developing machine learning technology that assists pathologists in making more precise diagnosis. Rising investments in AI diagnosis-based startups is one of the key indicators that depicts upcoming opportunities.

Key suggestions from the report:

Read 150 page research report with ToC on "Artificial Intelligence In Diagnostics Market Size, Share And Trends Analysis Report By Component (Software, Hardware, Services), By Diagnosis Type, By Region, And Segment Forecasts, 2020 - 2027" at: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-diagnostics-market

Moreover, increasing adoption of AI technology by hospitals and research centers for clinical diagnosis purpose is another factor propelling market growth. For instance, in July 2018, two national research institutes in Japan succeeded in implementing AI technology for detecting early stage stomach cancer with high precision rate of 95.0% for healthy tissues and 80.0% for cancer tissues. According to National Cancer Centre and Riken, AI technology took 0.004 seconds to identify whether obtained endoscopic image contains normal stomach tissue or early stage cancer tissue. Growing awareness regarding the technology is expected to boost the usage of AI in medical procedures.

Grand View Research has segmented the artificial intelligence in diagnostics market on the basis of component, diagnosis type, and region:

Find more research reports on Healthcare IT Industry,by Grand View Research:

Gain access to Grand View Compass,our BI enabled intuitive market research database of 10,000+ reports

About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

Contact:

Sherry James Corporate Sales Specialist, USAGrand View Research, Inc.Phone: +1-415-349-0058Toll Free: 1-888-202-9519Email: [emailprotected] Web: https://www.grandviewresearch.com Follow Us: LinkedIn | Twitter

SOURCE Grand View Research, Inc.

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Artificial Intelligence In Diagnostics Market Worth $3.0 Billion By 2027: Grand View Research, Inc. - PRNewswire

Technology headed by AI has been instrumental in augmenting human capacities and reinventing human lifestyle. Code-driven systems integrating information and connectivity have ushered a new era which was previously unimagined bringing untapped opportunities and unprecedented threats.

Technology experts across the world have predicted that networked artificial intelligence will amplify human effectiveness besides threating human autonomy, and capabilities. We are not far from the age of super intelligent AI where algorithms may match or even exceed human intelligence and capabilities on tasks which involve complex decision-making, sophisticated analytics, pattern recognition, reasoning and learning, language translation, visual acuity and speech recognition

Data Security

Modern enterprises generate data and most of that still battles against data abuse. Most AI tools are and will be dominated by companies and governments who are striving for profits or power. This leaves data silos and data lakes open rising fears of security against data mishandling.

Diminishing Human Cognition

Though many see AI to augment human capacities but some even predict the opposite. The increasing dependence on machine-driven networks may diminish human cognitive abilities to think for themselves, interact effectively with others and take decisions independent of automated systems.

Trade-off for the Inevitable

As AI algorithms have taken over decision making and predictions, humans may experience a loss of control over their ability to think and act. Decision-making on key aspects is automatically ceded to code powered black box tools. The drag and drop tools are not making decisions easy, as users know the context but do not understand the logic behind why the tools work. Thus, in this context, privacy and the power over choice; are scarified with no control over the processes.

AI and allied technologies have already achieved superhuman performance in a juncture of areas, and it is beyond doubt that their capabilities will improve over the years, probably very significantly in 10 years from now, by 2030. Aided by an access to vast data troves, bots powered by intelligent automation will surpass humans in their ability to take complex decisions. AI will drive a vast range of efficiency optimizations especially into highly rule-based chores which involve manpower.

Newer generations of citizen data scientists will become more and more dependent on networked AI structures and processes. Networked interdependence will, increase an enterprises vulnerability to cyberattacks. There will be a sharp gap between the digital haves and have-nots, especially those who are technologically dependent digital infrastructures. The next question will be to answer the commanding heights of the digital network infrastructures ownership and control.

Artificial Intelligence is empowering the ability for autonomous operation and the first thing which comes to mind is autonomous vehicles, but the applications are limitless. The combination of natural language processing, predictive analytics, and the world of intelligent sensors powered by IoT have had a pervasive impact in our daily lives.

Summing up, AI will be an integral component of an enterprise experience. Organisations will increasingly use and sometimes rely on AI systems to enhance their daily interactions with each other. In the next decade, AI will propel the powers of language translation and augmented creativity bringing a new dimension into digital transformation.

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About AuthorMore info about author

Kamalika Some is an NCFM level 1 certified professional with previous professional stints at Axis Bank and ICICI Bank. An MBA (Finance) and PGP Analytics by Education, Kamalika is passionate to write about Analytics driving technological change.

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The future of Artificial Intelligence and what it means to the Enterprise? - Analytics Insight