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DAN: TSX-V (Canada)JE9N: FSE (Germany)DRRSF: OTC (USA)

SAGUENAY, QC, April 8, 2021 /CNW Telbec/ - Arianne Phosphate (the "Company" or "Arianne") (TSXV: DAN) (OTC: DRRSF) (FRANKFURT: JE9N), a development-stage phosphate mining company, advancing the Lac Paul project in Quebec's Saguenay-Lac-Saint-Jean region, is pleased to announce significant advancements in the design of its future tailings facility. Arianne partnered with the Quebec Center of Geomatics (CGQ), to advance research and development on a new method for the design and future monitoring of the Company's tailings operations. This work will use geomatic and remote sensing tools combined with artificial intelligence that should greatly improve the safety aspects of Arianne's operations.

"The Lac Paul mine is projected to be one of the most environmentally friendly phosphate mines in the world," said Jean-Sbastien David, COO of Arianne Phosphate. "From the project's onset, Arianne's design process had the goal of constructing a mine using best environmental practices and, the integration of technology was vital in this regard. Further, our reliance on renewable hydro-electricity will allow us to greatly diminish our production of greenhouse gases [GHG] with the goal of ultimately being GHG neutral. Our most recent endeavors have also added to the safety and structural integrity of our tailings facility."

Brian Ostroff, CEO of Arianne Phosphate added, "we take seriously our responsibilities surrounding environmental and safety issues. We know that many challenges surrounding mining operations stem from failures at their tailings facilities and, our work here goes a long way towards reducing these threats. Arianne will produce a high-purity, low-contaminant phosphate concentrate that provides for society's needs but, in as safe and effective manner as possible."

Arianne partnered with the Quebec Center of Geomatics (CGQ), a group within the College of Chicoutimi, in the Province of Quebec, to develop a new way to use geomatic and remote sensing instruments and monitor this information through a solution that uses artificial intelligence. It is during the construction process that sensors will be built in throughout the tailings dam that will measure, in real-time, data points such as moisture and pressure and, make adjustments as necessary to allow for smooth and safe operations, allowing for greater safety.

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This research project was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) through its Partnership Engage Grants.

Qualified PersonJean-Sbastien David, P.Geo., Qualified Person by NI 43-101, has approved this release. Mr. David is also the Company's Chief Operating Officer.

About Arianne PhosphateArianne Phosphate ("Arianne Phosphate Inc.") (www.arianne-inc.com) is developing the Lac Paul phosphate deposits located approximately 200 km north of the Saguenay/Lac St. Jean area of Quebec, Canada. These deposits will produce a high-quality igneous apatite concentrate grading 39% P2O5 with little or no contaminants (Feasibility Study released in 2013). The Company has 173,354,669 million shares outstanding.

Neither TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.

Follow Arianne on:Facebook: https://www.facebook.com/ariannephosphateTwitter: http://twitter.com/arianne_danYouTube: http://www.youtube.com/user/ArianneResourcesFlickr: http://www.flickr.com/photos/arianneresourcesResource Investing News: http://resourceinvestingnews.com/?s=Arianne

Cautionary Statements Regarding Forward Looking Information

This news release contains "forward-looking statements" and "forward-looking information" within the meaning of applicable securities regulations in Canada and the United States (collectively, "forward-looking information"). Forward-looking information includes, but is not limited to, anticipated quality and production of the apatite concentrate at the Lac Paul project. Often, but not always, forward-looking information can be identified by the use of words such as "plans", "expects, "is expected", "budget", "scheduled", "estimates", forecasts", "intends", "anticipates", or "believes", or the negatives thereof or variations of such words and phrases or statements that certain actions, events or results "may", "could", "would", "might", or "will" be taken, occur or be achieved. Forward-looking information is subject to known and unknown risks, uncertainties and other factors that may cause the actual results, level of activity, performance or achievements of the Company to be materially different from those expressed or implied by such forward-looking information, including but not limited to: volatile stock price; risks related to changes in commodity prices; sources and cost of power facilities; the estimation of initial and sustaining capital requirements; the estimation of labour and operating costs; the general global markets and economic conditions; the risk associated with exploration, development and operations of mineral deposits; the estimation of mineral reserves and resources; the risks associated with uninsurable risks arising during the course of exploration, development and production; risks associated with currency fluctuations; environmental risks; competition faced in securing experienced personnel; access to adequate infrastructure to support mining, processing, development and exploration activities; the risks associated with changes in the mining regulatory regime governing the Company; completion of the environmental assessment process; risks related to regulatory and permitting delays; risks related to potential conflicts of interest; the reliance on key personnel; financing, capitalization and liquidity risks including the risk that the financing necessary to fund continued exploration and development activities at Lac Paul project may not be available on satisfactory terms, or at all; the risk of potential dilution through the issue of common shares; the risk of litigation. Forward-looking information is based on assumptions management believes to be reasonable at the time such statements are made, including but not limited to, continued exploration activities, no material adverse change in commodity prices, exploration and development plans proceeding in accordance with plans and such plans achieving their stated expected outcomes, receipt of required regulatory approvals, and such other assumptions and factors as set out herein. Although the Company has attempted to identify important factors that could cause actual results to differ materially from those contained in the forward-looking information, there may be other factors that cause results not to be as anticipated, estimated or intended. There can be no assurance that such forward-looking information will prove to be accurate, as actual results and future events could differ materially from those anticipated in such forward-looking information. Accordingly, readers should not place undue reliance on forward-looking information. Forward-looking information is made as of the date of this press release, and the Company does not undertake to update such forward-looking information except in accordance with applicable securities laws.

SOURCE Arianne Phosphate Inc.

Cision

View original content: http://www.newswire.ca/en/releases/archive/April2021/08/c6273.html

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Technological Innovation and Artificial Intelligence Will Provide for Increased Operational Safety at the Arianne Phosphate Project - Yahoo Finance

NEW YORK--(BUSINESS WIRE)--CB Insights today named Dataiku, the world's most advanced Enterprise AI platform, to the fifth annual AI 100 ranking, showcasing the 100 most promising private artificial intelligence companies in the world.

This is the fifth year CB Insights has recognized the most promising private artificial intelligence companies with the AI 100, and this is one of the most global groups we've ever seen. This year's cohort spans 18 industries, and is working on everything from climate risk to accelerating drug R&D, said CB Insights CEO Anand Sanwal. Last year's AI 100 companies had a remarkable run after being named to the list, with more than 50% going on to raise additional financing (totaling $5.2B), including 16 $100 million+ mega-rounds. Many also went on to exit via M&A, SPAC or IPO. As industry after industry adopts AI, we expect this years class will see similar levels of interest from investors, acquirers and customers."

Were honored to be included on this exceptional list of companies solving some of the worlds greatest challenges through AI, said Florian Douetteau, CEO of Dataiku. Its exciting recognition for our team, which since Dataiku was founded in 2013 has succeeded in creating a best-in-class data science and machine learning platform that democratizes AI within the enterprise.

Through an evidence-based approach, the CB Insights research team selected the AI 100 from a pool of over 6,000 companies based on several factors including patent activity, investor quality, news sentiment analysis, proprietary Mosaic scores, market potential, partnerships, competitive landscape, team strength, and tech novelty. The Mosaic Score, based on CB Insights algorithm, measures the overall health and growth potential of private companies to help predict a companys momentum.

Dataiku supports the AI strategies of more than 400 companies worldwide, enabling organizations across pharmaceuticals, healthcare, financial services, transportation, the public sector, manufacturing, retail, and more to massively scale their AI efforts. Dataiku employs more than 600 people worldwide between offices in New York, Paris, London, Munich, Sydney, and Singapore, and plans to hire another 300 employees in 2021. Its roots are in France, its headquarters is in New York, and its culture is a dynamic melting pot of all of its international influences.

Quick facts on the 2021 AI 100:

About CB Insights

CB Insights builds software that enables the world's best companies to discover, understand and make technology decisions with confidence. By marrying data, expert insights and work management tools, clients manage their end-to-end technology making process on CB Insights. To learn more, please visit http://www.cbinsights.com.

About Dataiku

Dataiku is one of the worlds leading AI and machine learning platforms, supporting agility in organizations data efforts via collaborative, elastic, and responsible AI, all at enterprise scale. Hundreds of companies use Dataiku to underpin their essential business operations and ensure they stay relevant in a changing world, including models driving fraud detection, customer churn prevention, predictive maintenance, supply chain optimization, and much more. Dataiku is built for companies looking to democratize AI across their organization, bringing agility and preparedness to the business through the use of data by everyone from analysts to data scientists.

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Dataiku Named to the 2021 CB Insights AI 100 List of Most Innovative Artificial Intelligence Startups - Business Wire

In summary

AB 13 would set criteria to minimize unfair, biased or discriminatory decisions by artificial intelligence systems used by government.

Assemblymember Ed Chau, a Democrat from Monterey Park, represents Assembly District 49, Assemblymember.Chau@assembly.ca.gov. Chau introduced Assembly Bill 13 and is chair of the Assembly Committee on Privacy and Consumer Protection.

Debra Gore-Mann is president and CEO of The Greenlining Institute, debra.goremann@greenlining.org. The Greenlining Institute is sponsoring Assembly Bill 13.

You cant see algorithms, but they can impact huge parts of your life, from seemingly minor things like what video YouTube will queue up next to life-and-death issues such as whether or not you can get a COVID-19 vaccination. Its time we all had a better idea how algorithms impact us, particularly when the government is using them.

An algorithm is simply a set of rules and instructions used by a computer program to perform a task or solve a problem. While algorithms themselves are coldly mathematical, they are created by humans who, like all of us, can have blind spots, biases or preconceptions. And that can lead to algorithms that make bad decisions or even perpetuate racial and gender bias.

These algorithms feed into an artificial intelligence framework where machine learning makes decisions and predictions from data about people decisions previously made by people. According to PwC research, artificial intelligence could contribute $15.7 trillion to the global economy by 2030.

The Greenlining Institute recently released an analysis of the problem, titled Algorithmic Bias Explained: How Automated Decision-Making Becomes Automated Discrimination, which included some startling findings. The report reviews a number of incidents that have made it into the media in which algorithms perpetuated discrimination based on race, gender or income and those reports represent just the tip of the iceberg, because most algorithms operate in the background, unseen and unknown by those whose lives they impact.

Some of the most disturbing reports have involved government programs, including an Arkansas Medicaid algorithm that wrongly cut off medical and nursing home benefits to hundreds of people. Another, used in Detroit, perpetuated old, discriminatory patterns of redlining by channeling community development funding away from the very neighborhoods that needed it most literally a case of algorithmic redlining.

In February, the New York Times reported serious issues with an algorithm the federal government uses to manage COVID-19 vaccine allocations: The Tiberius algorithm calculates state vaccine allotments based on data from the American Community Survey, a household poll from the United States Census Bureau that may undercount certain populations like undocumented immigrants or tribal communities at risk for the virus.

Equally concerning, the New York Times quoted researchers and health officials who are frustrated at how little they know about how the Tiberius algorithm decides how many vaccine doses to send where, describing it as a black box.

When government makes decisions that affect our daily lives, our communities and potentially even our very survival, those decisions should not be made in a black box.

Thats why weve worked to develop legislation that will begin to bring transparency to the use of algorithms by government agencies in our state. If passed, Assembly Bill 13 would set forth criteria for the procurement of high-risk automated decision systems by government entities in order to minimize the risk of adverse and discriminatory impacts resulting from their design and application. The bill is scheduled to be heard in the Assembly Committee on Privacy and Consumer Protection on April 8.

Specifically, the bill would require a prospective contractor to submit an Automated Decision System Impact Assessment to evaluate the privacy and security risks to personal information and risks that may result in inaccurate, unfair, biased or discriminatory decisions impacting individuals. It would also require the contracting entity to produce an accountability report, after awarding the contract, which includes a detailed mitigation plan for identifying and minimizing the potential for any disparate impacts, and would make both the assessment and report available to the public.

At their best, algorithms can do a tremendous amount of good. They have the potential to make decision-making faster, fairer and more data-driven. But weve ignored their dark side for too long.

Its time to shine some light in that black box. Lets make sure that when government uses algorithms to make decisions on everything from health care to public benefits, we know whats happening and that the process is accurate and fair.

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Assemblymember Ed Chau has also written about facial recognition regulation and about stopping hateful acts against Asian Americans.

Debra Gore-Mann has also written about California regaining its power to regulate internet service providers.

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Shine some light in black box of algorithms used by government - CalMatters