Archive for the ‘Artificial Intelligence’ Category

Artificial Intelligence and Satellite Technology to Enhance Carbon Tracking Measures – JD Supra

New carbon emission tracking technology will quantify emissions of greenhouse gas, holding the energy industry accountable for its CO2 output. Backed by Google, this cutting-edge initiative will be known as Climate TRACE (Tracking Real-Time Atmospheric Carbon Emissions).

Advanced AI and machine learning now make it possible to trace greenhouse gas (GHG) emissions from factories, power plants and more. By using image processing algorithms to detect carbon emissions from power plants, AI technology makes use of the growing global satellite network to develop a more comprehensive global database of power plant activity. Because most countries self-report emissions and manually compile results, scientists often rely on data that is several years out of date. Moreover, companies often underreport carbon emissions, rendering existing data inaccurate.

Climate TRACE addresses these issues by partnering with other leaders in sustainability practicesincluding former U.S. Vice President Al Gore, WattTime, CarbonPlan, Carbon Tracker, Earthrise Alliance, Hudson Carbon, OceanMind, Rocky Mountain Institute, Blue Sky Analytics and Hypervine. The Climate TRACE coalition aims to help countries in meeting Paris Agreement targets and place the world on a path to sustainability.

The carbon tracking efforts of Climate TRACE will result in a conglomeration of data to be made available to the public, which may assist plaintiffs in climate liability cases and lead to enhanced enforcement of environmental laws. The slow pace of international climate negotiations has led to an increase in lawsuits demanding action on global warming. As of this year, 1,600 climate-related lawsuits have been filed worldwide, including 1,200 lawsuits in the United States alone. Currently, climate liability cases rely predominantly on a database run by the Carbon Disclosure Project and the Climate Accountability Institute. This database, initially released in 2013 as the Carbon Majors Report, attempts to link carbon pollution to emitters. The 2013 report pinpointed 100 producers responsible for 71% of global industrial GHG emissions. Its 2017 report, for instance, indicated that 25 corporate and state producing entities account for 51% of global industrial GHG emissions. While the Carbon Majors Report has assisted in determining the largest carbon emitters on a global scale, Climate TRACE will provide more frequent and accurate monitoring of pollutants.

Data from Climate TRACE will also help hold countries accountable to the Paris Climate Agreement, expanding upon European efforts to monitor global warming. Early last year, a space budget increase put Europe in the lead to monitor carbon from space using satellite technology. In December 2019, member governments awarded the European Space Agency $12.5 billion. This substantial increase allowed the ESA to devote $1.8 billion to Copernicus, a satellite technology program which continuously tracks Earths atmosphere. The program allowed Europe to analyze human carbon emissions regularly. With Copernicus, the ESA became the only space agency to monitor pledges made under the Paris Climate Agreement. The Climate TRACE coalitionwith members spanning across three continentswill make carbon monitoring a global effort.

Climate TRACE has created a working prototype that is currently in its developmental stages. The coalition intends to release its first version of the AI project by the summer of 2021.

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Artificial Intelligence and Satellite Technology to Enhance Carbon Tracking Measures - JD Supra

Postdoctoral Research Associate in Artificial Intelligence job with DURHAM UNIVERSITY | 215559 – Times Higher Education (THE)

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.

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

How do CEO’s Succeed with Artificial Intelligence at their Workplace? – Analytics Insight

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

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

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

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

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:

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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