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Is a ban on TikTok possible and what would happen if it … – Grid

Can TikTok really be banned, as many politicians are now proposing? And what would be lost or gained by a prohibition of the wildly popular video-sharing platform which is used by millions of Americans and billions of people worldwide?

For some answers, Grid turned to David Greene, an attorney with the Electronic Frontier Foundation, a San Francisco nonprofit that promotes online users rights and supported a court challenge to efforts by the Trump administration to shut down TikTok. That effort ultimately floundered. The latest government threat to the social media behemoth comes from a bipartisan bill that gives President Joe Biden the power to ban TikTok, although so far the methodology of any ban is unclear.

It could mean stopping app stores from distributing downloads. It could mean forcing the sale of TikTok to a domestic company. The latest idea surfaced Wednesday from the Committee on Foreign Investment in the United States: force Chinese owners to divest their shares in TikTok. But according to experts, none of these approaches would do away with the app itself. And it beggars the imagination to think that the government would demand that everyone with TikTok on their phones simply stop using it.

Underpinning the regulatory zeal is the presumption that the Chinese-owned company ByteDance, which owns TikTok, would supply user data to the Chinese government or is already doing so. U.S. and European officials have cited national security risks, but so far, as Greene points out, the specifics of that risk have been kept from the public. So we dont know what the Chinese might be looking for or would get from users accounts. Greene and other First Amendment champions are quick to point out that the U.S. government must show a compelling interest to limit free speech as enjoyed by TikTok users, whether they are posting videos of their favorite Friday night outfits or engaging in political advocacy.

This interview has been edited for length and clarity.

Grid: Lets assume that TikTok goes away. Beyond the First Amendment concerns, what do you feel would be lost in terms of users rights and the whole cultural experience that it is brought to the country, particularly young people?

David Greene: TikTok is a major social influence at this particular moment. So its loss would be significant. Im not saying we would never recover; it hardly existed a few years ago. Its used by students. Its used by journalists, especially student journalists, quite broadly. It has academic uses. So it has very quickly become very embedded in our society.

G: Its so-called influencers can drive trends and commerce. TikTok content can be both serious and frivolous. User videos show everything from cute chipmunks, to gum-smacking and lip-syncing teens, to kids who change their outfits five times in one brief video. Beyond that, how would cultural exchange suffer?

DG: Any communications tool that allows people to reach a broad audience around the world, with very little technical skill and very little financial investment, is going to have an impact. There is also a great thirst for cultural exchange for organizing, for advocacy, around rights and around interests, or efforts at democratizing. So as weve seen with every social media platform that gains wide acceptance, these are very beneficial uses and effects that you would expect with people who very easily communicate and spread their ideas and identify community around the world.

G: Lets say the Chinese are hoovering up all this stuff. What is the value to anybody? Or is it a matter of getting embedded data that we dont even know about?

DG: Well, we dont know what the data will be useful for. But it could be a lot of things: Peoples social media habits tell a lot about their interests, and who they associate with, what things theyre likely to buy, what things are likely to catch their attention all of which can be beneficial for companies in terms of directing advertising and finding people were also recommending other content. And you can see how that could be useful to foreign actors, especially if they were trying to influence public opinion and want to make sure that certain people receive certain messages.

G: But TikTok users and other social media users are voluntarily giving this information away. So should the government do more regulation to prevent data mining by all social media companies?

DG: I dont want to downplay the importance of data privacy with respect to governance. Privacy is a human right, and people have a right to autonomy over their private information. I take that part of it very seriously. That being said, each person also has the role of threat modeling; they can determine to what extent, if they have enough knowledge about how their data is used, whether the threat that using the app poses is something thats acceptable for them. For many, many people, it might be a completely reasonable decision to say, you know, I understand that my data is being sucked up and it may end up in the hands of the Chinese government or might end at the hands of other governments. Others would say, I dont want to see it happen.

The important thing is giving them the autonomy to make that choice. And thats why if the government is really concerned about this, it should look at data privacy more broadly and enact more comprehensive data-privacy regulation that would restrict how all companies, not just TikTok, collect and retain and use user data. And so far, in Congress there seems to be bipartisan support for banning TikTok. And then not a lot of support for that type of comprehensive data privacy regulation

G: How could TikTok be effectively banned?

DG: I think the answer is, it depends on what the ban is. But if there were a total ban one of the things commonly discussed is banning the app stores from selling the app I think that would be making it less safe for users to use than more safe. One thing is that apps automatically set updates; if there are user privacy and data privacy vulnerabilities in the app, the company would correct that. Users who already had it on their devices get those updates.

The second thing that pretty likely happens is called using the side door. People will just find a way to install it from a website or otherwise not through the app store. And then you get the same problem that if there are security updates, they wont automatically get to the phones of those people. So you end up with a less-secure service, not a more-secure service. Another thing that could happen is just make it illegal to possess it. And I certainly dont see arresting people who have TikTok on their phone.

G: What else is possible?

DG: One other thing would be to force the sale of the company to U.S. interests. That doesnt necessarily solve data privacy problems, either, although maybe conceivably, it would address issues about closed or open channels with the Chinese government. It could potentially close that. But it doesnt actually mean that youre denying the Chinese government access to user data. So its very hard to see what a ban contributes. And obviously, when youre forcing a sale, that raises a lot of other issues. So it is hard to see exactly how you are putting in a ban.

G: I was talking to another First Amendment lawyer who said, roughly, this is all a publicity stunt by politicians. Would you agree with that?

DG: You know, I dont guess what peoples motives are for doing it. The way I see this is that the First Amendment does require that if youre going to say that U.S. people cant communicate with each other in a certain way, then that restriction, no matter what form it takes if its a ban on the app stores or making it illegal for the company to operate or a decision by Congress that they need to divest from foreign ownership whatever form it takes, that decision is going to have to satisfy First Amendment scrutiny. But no matter what level of scrutiny, the government is going to have to show that theres a real problem that they are trying to address and that this is an appropriately narrow approach. It has to be a real problem and not just be a suspicion or concern. Is this just political theater or is it xenophobia against all things China? Is it to score political points? We have to know what the basis for the restriction is.

G: One congressman described TikTok as a weather balloon into your phone. In other words, spyware.

DG: We dont know, right? We as American consumers dont know. Congress may know; they get a lot more information about spying and national security things. But you would think if they do know something theyd actually tell us instead of just dancing around it. But anyway, we do know theres a pretty legitimate concern for not just TikTok but the way all companies collect user data, and share it both among each other and in commerce, as well as it being available to governments. And this is a serious concern. There are a lot of things that you point to that a lot of social media apps and things we put on our phones could look like spy balloons.

G: The primary point people often jump on is the First Amendment concern, like you said, restricting speech of Americans. And you said theres a strict scrutiny of that. So how does that get resolved in a court?

DG: Presumably, what would happen is that TikTok itself or users would sue to invalidate the law. And some of these laws arent specific to TikTok for example the Restrict Act [the Restricting the Emergence of Security Threats that Risk Information and Communications Technology Act] creates a process thats not limited to TikTok. But whoever is subject to the law would come in and sue. Its true that what they could come in and say is, Look, we have a really, really serious important governmental interest. They could say, Look, theres a real interest, but we cant explain in open court because of national security concerns. They will likely be able to then submit their recommendation to the judge. So the judge can see it even if other parties dont get it or the general public.

G: Do you use TikTok?

DG: I havent actually been on TikTok myself. I dont have an account. Ive seen TikTok videos posted in other places. Theres a lot of things that are funny. There are things that are very political. There are some things I think are stupid and uninteresting to me. As far as I can tell, it has the full range of content.

G: How old are you?

DG: Fifty-eight. But I also want to say the trend with a lot of technology in general is that young people tend to adopt it and drive it into popularity. My choice not to download the app I dont know how much has to do with my age; I certainly know plenty of people my age and older than me who are on TikTok. Its just my personal choice to limit the social media that I spend time on.

G: So once the olds start using it, maybe it will just go away?

DG: If they always see my parents are on it, my grandparents, my third-grade teachers on it, they stop using it or at least stop using it in the way they did before and they find a platform where their peers are on it and people who they dont mind sharing different information with. Thats the trend weve seen with many services.

Thanks to Lillian Barkley for copy editing this article.

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NHS England tells trusts to upload patient data to Palantir by end of … – Computing

Hospitals in England have been told to pass patient data to Palantir, the US data mining firm thought to be in poll position to win a 480 million data management contract to create a Federated Data Platform (FDP).

That's according to news and campaigning site openDemocracy, which cites a letter from NHS England's deputy chief executive and chief financial officer Julian Kelly to NHS trusts.

In the letter seen by openDemocracy, Kelly tells the trusts to begin uploading patient information to a new centralised database called "Faster Data Flows" by the end of March. Faster Data Flows, which has been trialled since last summer, is based on Palantir's data integration and analytics platform Foundry.

The move is controversial for several reasons, the first being that the FDP contract has not yet been awarded. Other bidders include a consortium of UK companies that says it can fulfil the five-year contract for significantly less than the 480 million the government has budgeted. Having the data already effectively formatted for Palantir would give the US firm a significant advantage.

A second cause for concern is the impact on privacy and confidentiality. While NHS England has stated that all patient records have been psuedonimised and Palantir says it does not process identifiable data, it is widely accepted that identifying an individual from a medical record and a few other data sources is trivial. For this reason, pseudonimised data still counts as personal data under the GDPR and patients should have to opt in to sharing their data.

A third issue is the nature of Palantir, and the way it is seeking to extend its tentacles into the NHS.

The secretive Peter Thiel-founded and CIA-funded company, which has a background in government and corporate surveillance, was originally handed a 1 contract during the Covid pandemic to assist with vaccination and ventilator distribution, but Foundry has since found its way into multiple other parts of NHS England's operations. Last year, a leaked paper revealed Palantir's strategy of "buying its way" into the NHS via acquisitions if contract bids are blocked.

Once Palantir is embedded in the NHS, it would be very hard to displace.

"Every trust in England will be forced to integrate Foundry into their workflows," GP IT consultant and clinical informatics expert Marcus Baw told openDemocracy. "This means there has already been significant taxpayer investment in using Foundry.

He continued: "Trusts are busy, with limited IT team capacity, so they cannot afford to redo work. To me this means that the system will already have significant momentum towards Palantir and Foundry."

Tory MP David Davis tweeted: "Sharing this NHS data with Palantir raises serious concerns about the security of masses of sensitive personal data. Pseudonymisation does not allay these concerns. The Government must seek explicit approval from Parliament before proceeding."

Several campaigning groups are threatening legal action against NHS England over the 480 million FDP contract. The groups, which include legal firm Foxglove, the Doctors' Association, the National Pensioners Convention and campaign group Just Treatment, are demanding the government reveal what data will be shared.

Foxglove tweeted that the deal "looks like GPDataGrab on steroids", a reference to a previous attempt by NHS England to share patient data with big tech the General Practice Data for Planning and Research (GPDPR), which was abandoned after a public revolt.

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Process mining reinvented – why a consumer-grade user experience is a must have – Diginomica

( Lightspring - Shutterstock)

Process mining software is poised to become the trusted, daily digital assistant for every business. For it to take the final step however, we must bring the power of it to find and capture value to everyone in the business, and to do that we must reinvent process mining.

In an earlier article, I wrote about how process mining is being reinvented to deliver an end-to-end map of your business. Through a new approach called object-centric process mining (OCPM), we can produce process models that more accurately reflect the interconnectedness of modern business operations. With these object-centric models, we can visualize the complex relationships between objects as they flow through a single process and even see how multiple processes interact with each other. Analysis that isnt possible with traditional process mining.

OCPM makes process mining more powerful, but that power is only useful if it can be effectively used. For process mining to be the platform that drives performance excellence, we must put the technology in the hands of people across the organization.

For too long, process mining vendors built products that were designed more for IT professionals and data analysts than the non-technical business decision makers who can make actual process improvements. We must change this. We must democratize process mining with a user experience (UX) that enables everyone in the business to analyze and optimize processes right out of the box.

The ubiquitous business systems we use every day (email, word processors, spreadsheets, presentations, internet search) all followed this same tried and true path. They went from complex applications used by a few to simple apps used by almost everyone. And in doing so, these applications drove productivity gains across the organization and society in general.

Process mining technology has the same if not greater potential to improve organizational efficiency and drive business sustainability and in turn promote a more sustainable society.

Building enterprise apps that become essential for every user is no small feat. Successful software, business or consumer, must be powerful, scalable, responsive, secure and provide real value. However, these back-end characteristics often go unnoticed by the end user or are lumped together into a general feeling of the app works pretty well. Running smoothly is just table stakes. As my colleague Bill Detwiler wrote, todays users expect their corporate invoicing system to be as easy-to-use as a ride hailing app.

So the question isnt why, but how. How do you build enterprise software at consumer scale, and in doing so ensure the broad adoption of process mining? It starts by listening to the customer.

During my career, Ive worked in both the consumer space, at YouTube with Google, and the enterprise space, at Hyperion, Oracle and now Celonis. Whether youre building software for enterprise users or consumers, success depends on understanding where your customers are coming from. Thats why Ive always stressed the importance of building bridges between engineers and customers.

When engineers connect with their users, they learn what makes the customer successful, which in turn gets the creative juices flowing and enables innovation as they work to drive more delight with the install base. This is what my team and I are working on at Celonis. Were reimagining the process mining experience and making the technology more accessible for everyone.

At Celonis, were obsessed with understanding who our customers are, the work they are doing and the problems they are trying to solve. From the data analyst or process specialist to the line of business leader or executive, were building a user interface (UI) that flows naturally and guides each persona through what theyre trying to accomplish. The UI were building isnt just a boatload of features, but a series of guided journeys. We call this new version of process mining, Business Miner.

Business Miner is a new capability of Celonis EMS that enables non-technical business users to discover actionable process insights through a unique question-and-answer-based interface. Insights in hand, the interface allows users to share them with others within the organization and collaborate on and discuss them directly within Celonis. Additionally, new users are guided through a streamlined onboarding process.

Heres what this looks like in the real world. While looking at your companys accounts payable process, Business Miner could present your newly onboarded Head of AP with questions, such as: What is the breakdown of payments in early, late, and on-time? Curated visuals would then guide them to key insights and suggest follow-up questions, such as: What is the root-cause of my late payments? Your Head of AP could then share these process insights and discuss them with their team directly within Celonis.

Without Business Miner, process exploration like this would require the work of an analyst and often code, such as Celonis PQL. Likewise, collaborating on the process insights would often mean jumping out of Celonis and sending screenshots through email or your corporate messaging app.

This more powerful, more accessible process mining user experience isnt just theoretical. Companies are already using it to drive value. Alex Moro, Head of Process Re-engineering and Advanced Design at HSBC, says:

We see Celonis as a critical platform to drive business performance at HSBC.Removing the barrier to entry for non-technical users with Business Miner will help us better realize the value of Celonis EMS.

Now imagine if every single process and every single business ran a bit more efficiently. That can create more sustainable businesses and in turn a more sustainable world. As Ive said before, processes can save the world.

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Process mining reinvented - why a consumer-grade user experience is a must have - Diginomica

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Comstock Mining’s Return On Capital Employed Overview – Comstock (AMEX:LODE) – Benzinga

March 20, 2023 10:45 AM | 2 min read

Benzinga Pro data, Comstock Mining (AMEX:LODE) reported Q4 sales of $30 thousand. Earnings fell to a loss of $20.79 million, resulting in a 291.07% decrease from last quarter. In Q3, Comstock Mining brought in $39 thousand in sales but lost $5.32 million in earnings.

Return on Capital Employed is a measure of yearly pre-tax profit relative to capital employed by a business. Changes in earnings and sales indicate shifts in a company's ROCE. A higher ROCE is generally representative of successful growth of a company and is a sign of higher earnings per share in the future. A low or negative ROCE suggests the opposite. In Q4, Comstock Mining posted an ROCE of -0.37%.

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Keep in mind, while ROCE is a good measure of a company's recent performance, it is not a highly reliable predictor of a company's earnings or sales in the near future.

ROCE is a powerful metric for comparing the effectiveness of capital allocation for similar companies. A relatively high ROCE shows Comstock Mining is potentially operating at a higher level of efficiency than other companies in its industry. If the company is generating high profits with its current level of capital, some of that money can be reinvested in more capital which will generally lead to higher returns and, ultimately, earnings per share (EPS) growth.

For Comstock Mining, a negative ROCE ratio of -0.37% suggests that management may not be effectively allocating their capital. Effective capital allocation is a positive indicator that a company will achieve more durable success and favorable long-term returns; poor capital allocation can be a leech on the performance of a company over time.

Comstock Mining reported Q4 earnings per share at $-0.26/share, which did not meet analyst predictions of $-0.05/share.

This article was generated by Benzinga's automated content engine and reviewed by an editor.

2023 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.

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Predictive Analytics Best Practices | eWEEK – eWeek

Predictive analytics is the use of data and other tech tools like artificial intelligence (AI) and machine learning (ML) to predict future outcomes. Predictive analytics uses historical data to discover patterns and trends that predict future occurrences.

Currently, many industries are actively using predictive analytics, including manufacturing, healthcare, finance, education, retail, cybersecurity, and agriculture. For example, predictive analytics can be used for everything from predicting business revenue to machine downtime.

As data science evolves, new methods of using data are taking hold. Now, organizations can use data proactively through the use of predictive analytics.

Read more: What is Predictive Analytics?

For organizations ready to take advantage of predictive analytics, there are several best practices to follow for success. These include identifying objectives, testing predictive models, and making continuous improvements.

The first step organizations should take is to define objectives for using predictive analytics. This involves outlining what the organization wants to predict, which will inform how predictive models are developed. These objectives should align with overarching business goals.

For example, if one business goal is to reduce operating expenses, predictive analytics models could predict unnecessary costs such as downtime.

Organizations must also define the key metrics theyll use to ensure the success of their data initiatives. These are the key performance indicators (KPIs) that show progress toward predictive analytics objectives.

For the example above, KPIs for reducing operating expenses may include total expenses or operational expense ratio (OER). Organizations should stick to measuring only the KPIs that align with their predictive analytics and business objectives.

A high-quality prediction requires high-quality data. The data sets used for predictive analytics must be accurate, large, and relevant to the objectives.

For the best results, organizations must have access to both historical data and real-time data, as well as both structured and unstructured data.

To build a data set, organizations should extract data from all relevant sources, clean the data in preparation for analysis, and place that data inside a data warehouse. Or, data virtualization tools can aggregate data from disparate sources into one location.

For more information, also see: Four Pillars of a Successful Data Strategy: Making Better Business Decisions

Before using predictive analytics models to predict outcomes, they must be thoroughly tested or validated. Otherwise, predictions may be inaccurate and result in poor business decisions.

Organizations should run tests using sample data sets to determine the accuracy of predictions first. Once a predictive model is proven to be accurate, it can then be put to use.

After testing and deploying predictive models, insights that are uncovered must be put to proper use. Organizations should document what occurs with insights and whos responsible for employing them.

Some questions to consider include:

Data changes over time and predictive models should follow suit. Organizations must monitor predictive model performance and make continuous improvements for the best results. This ensures models remain useful and accurate.

There are various ways organizations can improve their predictive models. For example, they can add more data to the models data set or re-tune, re-train, and re-test the model to determine areas that are in need of improvement.

The last step is to actually implement the software. There are a number of predictive analytics software tools that can be deployed. Examples include:

For moreinformation, also see: Best Data Analytics Tools

There are three predictive analytics models that are most commonly used:

Classification: Classification models categorize data to show relationships within a dataset. These models are used to answer questions with binary outputs like yes or no.

Clustering: Clustering models group data based on attributes without human intervention.

Time series: Time series models work to analyze data points that are collected over specific time periods, such as per hour or daily.

Once these models are planned, predictive analytics is quite simple. First, data is collected based on the type of prediction an organization wants to make. Then, one of these statistical models is developed and trained to predict outcomes using the collected data.

Once the model generates any kind of prediction, it can then be used to inform decisions. Through automation, some predictive models can even be instructed to perform actions based on predictions.

Predictive analytics takes data analysis a step further. While basic data analysis can show us what happened and what to do about it, predictive analytics shows us what could happen and how we can intervene.

Predictive analytics offers a wide range of benefits across industries, from manufacturing to cybersecurity.

The average automotive manufacturer stands to lose $22,000 per minute during unplanned production downtime. Fortunately, through predictive analytics, manufacturers can make unplanned downtime a thing of the past.

Predictive analytics models can use historical data to find patterns that result in machine breakdowns, required maintenance, etc. Manufacturers can then mitigate risks before they result in costly downtime.

The healthcare industry can benefit from predictive analytics in many ways. For example, predictive models can be used to determine a patients risk factors for diseases such as diabetes and heart disease. As a result, physicians can provide better preventative care.

Retailers must be privy to what customers want to drive revenue. Thats why many retailers are turning to predictive analytics to improve product availability.

For example, predictive models can predict which products that will be in higher demand during certain seasons. Retailers can then ensure they have adequate inventory to deliver on customer needs.

Cyber attacks can be seriously damaging to any organization. According to research by IBM, the average data breach costs $9.44 million on average. Predictive analytics can support organizations in minimizing and even preventing damage.

For example, predictive models can pinpoint trends that indicate potential risks. Organizations can then improve security in these areas to prevent attacks and data loss.

For moreinformation, also see:Data Mining Techniques

As mentioned earlier, the predictive analytics market is expected to grow quickly in the next five years. But what does the future look like?

Predictive analytics will continue to gain in popularity. And as technology such as machine learning and AI become more widely accessible, more organizations, both large and small, will be able to take advantage of predictive analytics.

Predictive analytics will lead the charge in pioneering the use of other forms of data analytics, such as prescriptive analytics. This method not only predicts outcomes but instructs organizations on the actions they should take in relation to the outcomes.

What comes next? For now, organizations must develop data analytics strategies that fit their goals and make room for new, forward-looking analytics methods as they evolve.

Also see: What Is Descriptive Analytics?

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10 Best and High-Paying AI Jobs for 2023 – NASSCOM Community

Artificial intelligence (AI) has created new opportunities in recent years. Industries are being affected, making previously unthinkable activities like space travel and melanoma diagnosis viable. As a result, there has also been a continuous rise in AI careers. LinkedIn said AI professionals would be among the 'jobs on the rise' in 2023. The 10 fantastic and well-paying AI jobs you can pursue in 2023 and beyond are discussed in this blog post. Also, do have a look at the online data science certification course if you want to start a career in data science and AI.

The future of AI employment is really bright. The US Department of Labor Statistics anticipates an 11% increase in computer science and information technology employment between 2019 and 2029. The industry will gain roughly 531,200 new employees as a result. It would seem that this is a conservative estimate. "AI and Machine Learning Specialists" are the second most in-demand profession according to the World Economic Forum.

As the industry matures, AI jobs will diversify, increase in quantity, and become more complicated. This will open up opportunities for experts, including novice and senior researchers, statisticians, practitioners, experimental scientists, etc. The future of moral AI is also brightening.

Artificial intelligence is a young and specialized field, yet many different careers exist. There are many different types of careers in AI, each requiring a unique set of qualifications. Let's examine each of the top ten in turn.

Data scientists and software engineers work together to create the field of machine learning engineering. Using big data technologies and programming frameworks, they produce scalable data science models capable of handling terabytes of real-time data and production-ready.

Qualifications suitable for work as a machine learning engineer include data science, applied research, and software engineering. Applicants for AI positions should have a strong mathematical foundation and be knowledgeable in deep learning, neural networks, cloud applications, and Java, Python, and Scala programming. Understanding IDE software development tools like Eclipse and IntelliJ is also beneficial.

Data scientists collect data, analyze it, and make judgments for a number of purposes. They utilize a variety of technical procedures, tools, and algorithms to draw information from data and identify significant patterns. This could entail anything as simple as spotting anomalies in time-series data or something more complicated like making predictions about the future, giving advice. The following qualifications are crucial for a data scientist:

BI developers look into complex internal and external data to find trends. For instance, a business that provides financial services could be a person who keeps track of stock market data to aid in investment selection. This might be someone who keeps an eye on sales patterns for a product company to help with distribution plans.

Business intelligence developers, unlike data analysts, do not construct reports. In order to use dashboards, business users are usually in charge of creating, modeling, and managing complex data on readily accessible cloud-based data platforms. Specific skills are expected of a BI developer:

A research scientist is one of the AI occupations with the highest academic demands. They pose original, thought-provoking queries for AI to respond to. They are specialists in various fields related to artificial intelligence, such as statistics, machine learning, deep learning, and mathematics. Like data scientists, researchers also require a computer science doctorate.

Organizations looking to hire research scientists to anticipate them to be well-versed in these fields, as well as in graphical models, reinforcement learning, and natural language processing. Benchmarking expertise and familiarity with parallel computing, distributed computing, machine learning, and artificial intelligence are preferred.

Big data engineers and architects build ecosystems allowing efficient connectivity among many business verticals and technologies. Although big data engineers and architects are often entrusted with planning, creating, and developing big data environments on Hadoop and Spark systems, this profession may feel more complicated than that of a data scientist.

Most employers prefer professionals with a Ph.D. degree in mathematics, computer science, or a closely related field. Yet, because this is a more practical role than, for example, a research scientist, practical experience is generally regarded as a vital substitute for a lack of academic degrees. Big data engineers require programming knowledge in C++, Java, Python, or Scala. Also, they must learn about data migration, visualization, and mining.

For AI applications, software engineers create software. They combine development operations such as writing code, continuous integration, quality control, API management, and so on for AI employment. They design and administer the software that architects and data scientists utilize. They stay up to date on the latest advances in artificial intelligence technologies.

An AI software engineer must be proficient in software engineering and artificial intelligence. They must have programming capabilities in addition to statistical and analytical abilities. Employers frequently require a bachelor's degree in computer science, engineering, physics, mathematics, or statistics.

Software architects develop and maintain technical standards, platforms, and tools. AI software architects do this for AI technology. They design and maintain the AI architecture, organize and carry out the solutions, select the tools, and ensure the data flow is seamless.

AI-driven organizations require software architects to have a bachelor's degree in computer science, information systems, or software engineering. Experience is just as important as knowledge in terms of actual application. You will be well-positioned if you have practical experience with cloud platforms, data operations, software development, statistical analysis, and so on.

A data analyst collects, cleans, processes, and analyzes data to draw conclusions. In the past, these were primarily routine, monotonous chores. The advent of AI has led to the automation of many routine tasks. As a result, a data analyst must be more familiar with data analytics than just spreadsheets. They must be knowledgeable about the following:

When industrial robots initially gained prominence in the 1950s, robotics engineers were possibly among the first jobs in artificial intelligence. Robotics has come a long way, from manufacturing lines to teaching English. Robotic-assisted surgery is used in healthcare. Personal assistants are being produced using robotic humans. A robotics engineer can do all of this and more.

Robotics engineers design and maintain AI-powered robots. Organizations usually require graduate degrees in engineering, computer science, or a related field for these positions.

Natural language processing (NLP) specialists are artificial intelligence (AI) engineers specializing in spoken and written human language. Engineers who work on voice assistants, speech recognition, document processing, and other projects employ NLP technology. For NLP engineering, organizations require a particular degree in computational linguistics. Companies may also be interested in hiring applicants with computer science, mathematics, or statistics backgrounds.

An NLP engineer would need knowledge of, among other things, sentiment analysis, n-grams, modeling, general statistical analysis, computer capabilities, data structures, modeling, and sentiment analysis. Prior knowledge of Python, ElasticSearch, web programming, and so on can be useful.

The vast majority of contemporary technology jobs are not in AI. Because artificial intelligence is a continuously evolving profession, experts in the area must constantly update themselves and keep up with new advances. AI/ML experts must keep up with the latest research and understand new algorithms on a regular basis; simply learning skills is no longer sufficient.

Furthermore, AI is under severe social and governmental scrutiny. AI professionals must

address the social, cultural, political, and economic consequences of AI and its technical components. The capacity to complete projects distinguishes an AI specialist in the real world. Experience is the only source for this

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ACME Lithium Inc. to Present at 121 Mining Conference in Las Vegas, Nevada March 28th and 29th – Yahoo Finance

Vancouver, British Columbia--(Newsfile Corp. - March 20, 2023) - ACME Lithium Inc. (CSE: ACME) (OTCQX: ACLHF) (the "Company", or "ACME") is pleased to announce that President and CEO Steve Hanson will be meeting and presenting to investors at 121 Mining Conference in Las Vegas, Nevada.

The 121 Mining Investment Las Vegas Summit takes place on March 28th and 29th and attracts US and international investors for two days of investment-led panel sessions and CEO presentations.

With the rapid demand for securing a domestic supply of lithium, Nevada is at the forefront of mining in the US and remains one of the world's most attractive jurisdictions for mining investment.

ACME's CEO Steve Hanson will be presenting an overview of ACME's two Nevada projects including an update on the Phase 2 lithium brine drill program at Clayton Valley, the recent geological field review and sampling programs at Fish Lake Valley, as well as information on ACME's Manitoba and Saskatchewan pegmatite projects in Canada.

About ACME Lithium Inc.

Led by an experienced team, ACME Lithium is a mineral exploration Company focused on acquiring, exploring, and developing battery metal projects in partnership with leading technology and commodity companies. ACME has acquired or is under option to acquire a 100-per-cent interest in projects located in Clayton Valley and Fish Lake Valley, Esmeralda County Nevada, at Shatford, Birse, and Cat-Euclid Lakes in southeastern Manitoba, and at Bailey Lake in northern Saskatchewan.

On behalf of the Board of Directors

Steve HansonChief Executive Officer, President and DirectorTelephone: (604) 564-9045info@acmelithium.com

For Investor Inquiries:Anthony SimoneSimone CapitalTelephone: (416) 881-5154asimone@simonecapital.ca

Neither the CSE nor its regulations service providers accept responsibility for the adequacy or accuracy of this news release. This news release may contain forward-looking information within the meaning of applicable securities laws ("forward-looking statements"). Forward-looking statements are statements that are not historical facts and are generally, but not always, identified by the words "expects," "plans," "anticipates," "believes," "intends," "estimates," "projects," "potential" and similar expressions, or that events or conditions "will," "would," "may," "could" or "should" occur and in this news release include but are not limited to the attributes of, timing for and expected benefits to be derived from exploration, drilling or development at ACME's project properties. Information inferred from the interpretation of drilling, sampling and other technical results may also be deemed to be forward-looking statements, as it constitutes a prediction of what might be found to be present when and if a project is actually developed. ACME's project location adjacent to or nearby lithium projects does not guarantee exploration success or that mineral resources or reserves will be defined on ACME's properties. Exploration, development, and activities conducted by regional companies provide assistance and additional data for exploration work being completed by ACME. These forward-looking statements are subject to a variety of risks and uncertainties which could cause actual events or results to differ materially from those reflected in the forward-looking statements, including, without limitation: risks related to fluctuations in metal prices; uncertainties related to raising sufficient financing to fund the planned work in a timely manner and on acceptable terms; changes in planned work resulting from weather, logistical, technical or other factors; the possibility that results of work will not fulfill expectations and realize the perceived potential of the Company's properties; risk of accidents, equipment breakdowns and labour disputes or other unanticipated difficulties or interruptions; the possibility of cost overruns or unanticipated expenses in the work program; the risk of environmental contamination or damage resulting from the Company's operations and other risks and uncertainties. Any forward-looking statement speaks only as of the date it is made and, except as may be required by applicable securities laws, the Company disclaims any intent or obligation to update any forward-looking statement, whether as a result of new information, future events or results or otherwise.

To view the source version of this press release, please visit https://www.newsfilecorp.com/release/159049

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ACME Lithium Inc. to Present at 121 Mining Conference in Las Vegas, Nevada March 28th and 29th - Yahoo Finance

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Predictive Analytics Market to Exceed US$44.3 Billion By 2030, In … – GlobeNewswire

New York, March 19, 2023 (GLOBE NEWSWIRE) -- ThePredictive Analytics Market report by Reports Insights reveals that the market generated a revenue of USD 13.5 billion in 2022and is anticipated to achieve USD 44.3 billion by 2030, displaying a CAGR of 18.5%. The report highlights the surging deployment of predictive analytics solutions across diverse industries and the mounting requirement for data-driven decision-making approaches.

Predictive Analytics Market Size, Share & Trends Analysis, By Solutions (Solution and Services), Deployment Type (On-Premise and Cloud), Enterprise Size (Small & Medium Enterprises, Large Enterprises), End-Use (Aerospace & Defense, Automotive & Transportation, BFSI, Healthcare, IT & Telecommunication, Media & Entertainment, Retail & E-commerce, Others), By Region and Segment, Forecast Period 2023 2030.

ReportsInsights Consulting Pvt. Ltd. has provided a detailed research report on the predictive analytics market, which takes into account various aspects such as market trends, value and supply chain, size, and regulatory environment. The report also analyzes the latest developments and growth opportunities in significant segments, including component, deployment type, enterprise size, end-use, and region. These factors are critical for market players to strengthen their competitiveness through mergers and acquisitions, strategic partnerships, and innovative product launches to bolster their market standing and keep up with evolving advancements in technologies.

Apply For Free Sample Report@https://www.reportsinsights.com/sample/673842

Predictive Analytics MarketGrowth Drivers:

Restraints

Competitive Landscape

As per the research, the major players in the predictive analytics market include IBM Corporation, Oracle Corporation, SAP SE, SAS Institute, Inc., Microsoft Corporation, Cloud Software Group, Inc., and Siemens. These companies offer various predictive analytics solutions, such as data mining, machine learning, and forecasting, and others to cater to the increasing demand for predictive analytics tools. The market is divided into two categories: pure-play vendors and full-suite vendors. Pure-play vendors specialize in predictive analytics and offer solutions that are specifically designed for this purpose. However, full-suite vendors provide a range of analytics solutions, including predictive analytics, as part of a larger suite of products.

Recent Developments:

In October 2022, Informatica, a frontrunner in enterprise cloud data management, was announced as one of the initial partners of Microsoft Intelligent Data Platform Partner Ecosystem. The introduction of such ecosystem was revealed by Microsoft at Microsoft Ignite 2022 event, and reflects the commitment of both companies towards supporting businesses in effectively leveraging AI with secure and well-managed data.

In October 2022, Google announced a range of innovations in AI and ML, data analytics and security at Google Cloud Next 2022. Google's objective was to offer a data cloud that is highly adaptable, accessible, and resilient that enables businesses to utilize their data from various sources, storage formats, and analytics techniques across different cloud providers and platforms that suit their preferences.

Immediate Delivery Available, Inquiry or Customization Request @https://www.reportsinsights.com/enquiry/673842

Predictive Analytics MarketSnapshot :-

Asia-Pacific[China, Japan, India, Southeast Asia, Korea, Western Asia]

South America[Brazil, Argentina, Columbia, Chile, Peru]

Europe[Germany, UK, Turkey, Spain, France, Italy, Russia, Netherlands, Switzerland]

Middle East & Africa[GCC, North Africa, South Africa]

Governments are also promoting the adoption of predictive analytics in various industries. For instance, the US government launched several initiatives to promote the use of big data and advanced analytics in healthcare and other sectors. This is expected to drive the demand for predictive analytics solutions in the coming years.

Growing adoption of cloud-based data warehouses for predictive analytics will push the market statistics in upcoming years. For instance, two of the worlds largest cloud service providers (Amazon and Google) offer a minimum up-time of more than 99.95%. Amazon for EC2 Servers and Google for Cloud Storage and BigQuery.

The vast amounts of data generated by digital technologies, social media, and the internet of things (IoT) will also create large pools of data that is used to train predictive models.

Rising usage of predictive analytics in new and innovative ways such as fraud detection, supply chain optimization, and predictive maintenance will create favorable opportunities for the demand for such technologies.

Increased importance of real-time for organizations to make quick decisions based on rapidly changing data will push the statistics of predictive analytics solutions and services to respond and address rapid changes in business environment.

The availability of powerful computing resources, and big data analytics tools even as open-source software and cloud-based analytics platforms will create lucrative opportunities for market growth in terms of more accessibility and affordability for predictive analytics.

Key Market Takeaways

Browse Full Report @https://www.reportsinsights.com/industry-forecast/global-predictive-analytics-market-statistical-analysis-673842

List of Major Predictive Analytics Market Players

Cloud Software Group, Inc.

Microsoft Corporation

Google Cloud

Augury Inc.

CFD Research Corporation

Oracle

SAS Institute Inc.

Siemens

IBM

ALTERYX, INC.

Axtria

Global Predictive Analytics Market Segmentation:

Key Questions Covered in the Predictive Analytics Market Report

What is the current size of predictive analytics market?

What is the expected CAGR of global market of predictive analytics from 2023 to 2030?

What factors drive the predictive analytics market growth?

Which region is expected to boost the market statistics in terms of value and volume?

Which major players function in the current market circumstances?

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Amid Pope Francis’ anniversary, Catholics need a new ‘Faithful … – National Catholic Reporter

For decades, timed with each U.S. presidential election cycle, the U.S. bishops regularly drafted a guide for faithful political engagement. That stopped with the papacy of Pope Francis. Why is unclear. As we celebrate the 10th anniversary of Francis' election, what is clear is the need for a new document, one that speaks to the sweeping changes that have occurred in America and globally, and one that reflects this papacy's sharpening of church teachings about the role of the church in the world.

The last guide, "Forming Consciences for Faithful Citizenship," was drafted in 2007 amidst lingering Catholic division following John Kerry's 2004 presidential candidacy and that elections Communion wars. It reads like a time capsule of that era. While much should be admired about "Faithful Citizenship," America and the world have seen dramatic changes in the intervening years.

In 2007, Benedict XVI was pope. The Gulf War was raging. The first iPhone appeared and social media was in its infancy. AI, data mining and gene editing were not yet things. Human-caused climate change was a theory still in doubt. Roe was still settled law; LGBTQ rights were not. It was written before the Great Recession, #OccupyWallStreet, #MeToo, the Arab Spring, Black Lives Matter, fake news, Russia's invasions of Ukraine, surging white Christian nationalism and before Jan. 6.

The year 2007 also marked a meeting of Latin American bishops in Brazil, at Aparecida, from which a pastoral theology emerged, championed by Cardinal Jorge Mario Bergoglio. Six years later he would be pope and that theology refocused the church's role in public life.

Putting the Gospels ahead of canon law, Aparecida theology takes Christ at his word in Luke's Gospel where he reads from Isaiah, "The Spirit of the Lord is upon me, because he has anointed me to bring glad tidings to the poor." Francis speaks similarly of Matthew 25 and the Beatitudes, as the "twin pillars of Christianity." Within days of the papal election Francis remarked, "Oh, how I would like a poor Church, and for the poor," reflecting the heart of Aparecida theology and offering a touchstone for rewriting "Faithful Citizenship."

Since the early Church Fathers, Christianity has taught that politics must be for the common good of the whole community. Inspired by the Gospels, Aparecida offers the gauge of the common good to be the lived life of the poor. That insight bears repeating: The measure of the common good is the lived life and dignity of the poor. The measure of civilization is the life and dignity of the poorest among us.

The poor of whom the Gospels speak are not only those without money. They are those on the peripheries of society the ignored, powerless, oppressed, discriminated against, immigrants and refugees, racial minorities, the imprisoned, the elderly, the sick, those not yet born and even abused creation itself.

Christian citizenship calls us to measure engagement in public life for what it means for the life and dignity of these poor. Every law, policy, institutional procedure and social norm must reflexively and continuously be considered against the criterion that is the real lives of these "poor."

If this sounds like charity, it is. Reiterating his predecessors, Francis locates politics among the highest forms of charity. Yet, charity (caritas) cannot be downward-looking pity that reinforces marginalization. Politics as charity must open itself to those on the periphery and bring them into communion, brotherhood and sisterhood, and into a just equality with all.

As Francis explains in Amoris Laetitia, this is done by: welcoming, accompanying, discerning situations and integrating. It is also synodal inasmuch as the church's role in public life is not to judge, but to be open to the world (never closed), listen and dialogue. True politics is caritas, directed toward the common good, the measure of which is the life of the poor.

Would this mean that the work of governing and political engagement should never be concerned about other matters like the economy, transportation, agriculture or even the military? Not at all. It means that such policies can only be right when they improve or at a minimum do not further harm those whom Christ in Matthew 25 calls the "least" among us.

Previous political guides from the U.S. bishops were informed by canon law, judging policies and candidates against church ordinances. The Holy Father, however, has remarked that church teaching is best without "shall nots," that instead a genuine encounter with the word of God and with the person of Jesus Christ must be foundational much as Aparecida theology emphasizes the Gospels. Similarly, a new "Faithful Citizenship," informed essentially by concern for the poor, would put evangelization and a positive vision for Christian political life center stage.

The Holy Father criticizes the idea of Catholic or Christian political parties and utterly rejects any imagining of Christian political life as a crusade of holy warriors against sinners. In his encyclical Fratelli Tutti and elsewhere, he speaks of "a better kind of politics" in contrast to the low-form politics too often seen in practice.

A better kind of politics is not ideological, not partisan, open to dialogue (not closed in self-righteousness), directed to the common good (not private interests), wielding caritas (not power), and ever intent on building bridges rather than walls of us-versus-them. Understood in this way, he reaffirms traditional church teaching on the true nobility of politics and public service.

It might be objected that rewriting "Faithful Citizenship" from the Gospels' emphasis on the poor lacks the specificity and juridical edge that came with terms such as "intrinsic evil," "material cooperation" and "non-negotiable." Yet, with the lived life of the poor as the measure of the common good, a wide-ranging, comprehensive theory of government and politics can be discerned and a general vision for promoting policies and laws is evident.

With the lived life of the poor as the measure of the common good, a wide-ranging, comprehensive theory of government and politics can be discerned and a general vision for promoting policies and laws is evident.

Concerned with lifting up the marginalized and bringing those on the peripheries into solidarity, and recognizing the equal dignity of all and empowering the powerless, the Aparecida approach would support democracy for all, diverse inclusivity, expansive human rights and popular sovereignty. Accordingly, the power of the state would also be limited and checked. These are the earmarks of liberal governance.

Similarly, a broad vision for policies is evident the Aparecida approach. It would encompass everything from assisted housing and health care to education and employment. Welcoming refugees and migrants, caring for creation, peacebuilding, anti-racism and developing an economic system that does not overly reward some while impoverishing others these too are evident policies of a noble politics measured by what we do for the life and dignity of those on the peripheries.

"Faithful Citizenship" was written for a different time, amid different demands for faithful citizenship. It was written before Pope Francis offered the church his insight for refocusing the role of the church in public life. American Catholics need a new document, one that speaks to our new times and one that reflects the teachings of this papacy.

Editor's note:Schneck's views are his own and do not necessarily reflect the views of theUnited States Commission on International Religious Freedom.

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Amid Pope Francis' anniversary, Catholics need a new 'Faithful ... - National Catholic Reporter

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Adventus Mining and Salazar Resources Announce Additional El … – Junior Mining Network

TORONTO, March 20, 2023 /CNW/ - Adventus Mining Corporation ("Adventus")(TSXV: ADZN) (OTCQX: ADVZF) and Salazar Resources Limited ("Salazar")(TSXV: SRL) (OTCQB: SRLZF) (collectively the "Participants") are pleased to announce additional infill drilling results from the underground portion of the El Domo volcanogenic massive sulphide deposit ("El Domo") located within the 21,537-hectare Curipamba project in central Ecuador.

Highlights Drill Results from the El Domo Deposit at Curipamba:

Drill hole CURI-412 intersected a thick section of massive sulphide from 200.27 to 214.46 metres, grading 3.13% copper, 0.79 g/t gold, 4.02% zinc, 27.9 g/t silver including a 1.18 metre subset from 200.27 to 201.45 metres with 5.25% copper, 1.31 g/t gold, 2.74% zinc, and 147.2 g/t silver. The highest gold and zinc values are on the upper part of the massive sulphide but the copper values continue down to 214.46 metres.

Drill Hole

From

(m)

To

(m)

Thickness

(m)

Cu(%)

Au(g/t)

Zn

(%)

Ag(g/t)

Pb(%)

CopperEquivalency(%) (1) (2)

Approx. TrueThickness (m)

CURI-412

200.27

214.46

14.19

3.13

0.79

4.02

27.9

0.00

4.44

13.71

including

200.27

201.45

1.18

5.25

1.31

2.74

147.2

0.00

6.69

1.13

(1)

Metal equivalency based on US$4.00/lb Cu, US$1,886.20/oz Au, US$1.36/lb Zn, US$22.06/oz Ag and US$0.93/lb Pb. Prices taken from 6-month contracts for precious metals and 3-month contracts for base metals from the London Metal Exchange, dated February 17, 2023.

(2)

Metal equivalency adjusted for metal recoveries based on detailed metallurgical data from Feasibility Study filed on SEDAR, effective data October 26, 2021. The report is titled "NI 43-101 Technical Report, Feasibility Study, Curipamba El Domo Project, Central Ecuador".

Drill hole CURI-413 intersected a massive sulphide section from 191.11 to 193.48 metres grading 5.06% copper, 0.80 g/t gold, 1.18% zinc, 9.3 g/t silver and 0.01% lead. The mineralization is present in the form of large clasts within a dacite breccia possibly due to replacement. It is an eastern continuation to the mineralization of the historical CURI-160 which had nearly 11 metres of massive sulfide.

Drill Hole

From

(m)

To

(m)

Thickness

(m)

Cu(%)

Au(g/t)

Zn(%)

Ag(g/t)

Pb(%)

CopperEquivalency(%)(1) (2)

Approx. TrueThickness (m)

CURI-413

191.11

193.48

2.37

5.06

0.80

1.18

9.3

0.01

4.29

2.26

(1)

Metal equivalency based on US$4.00/lb Cu, US$1,886.20/oz Au, US$1.36/lb Zn, US$22.06/oz Ag and US$0.93/lb Pb. Prices taken from 6-month contracts for precious metals and 3-month contracts for base metals from the London Metal Exchange, dated February 17, 2023.

(2)

Metal equivalency adjusted for metal recoveries based on detailed metallurgical data from Feasibility Study filed on SEDAR, effective data October 26, 2021. The report is titled "NI 43-101 Technical Report, Feasibility Study, Curipamba El Domo Project, Central Ecuador".

Drill hole CURI-414 intersected a section of semi-massive and massive sulphide separated by a low-grade fault zone, all between 192.95 to 204.55 metres grading 1.10% copper, 0.51 g/t gold, 0.5% zinc, 19.5 g/t silver and 0.01% lead. The lower 0.94 metre is high-grade copper, grading 7.45% copper, 0.82 g/t gold, 5.47%zinc, 78.3 g/t silver, and 0.09% lead. This drill hole is an extension of the mineralization in the eastern portion of the underground resource.

Drill Hole

From

(m)

To

(m)

Thickness

(m)

Cu(%)

Au(g/t)

Zn(%)

Ag(g/t)

Pb(%)

CopperEquivalency(%) (1) (2)

Approx. TrueThickness (m)

CURI-414

192.95

204.55

11.6

1.10

0.51

0.50

19.5

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Adventus Mining and Salazar Resources Announce Additional El ... - Junior Mining Network

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