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Here of the future of AI technology

Artificial intelligence is already pervasive in our digital life, from cell phones to chatbots. You just don’t realise it yet. The popularity of AI is growing, thanks in part to the vast amounts of data that machines can collect about our interests, purchases, and activities on a daily basis. Artificial intelligence researchers utilise all of this information to teach machines how to understand and predict whatever we want or don’t want. Let’s take a look at where AI is headed in the future.

Entertainment

Netflix, step aside. In the future, you could relax on your couch and order a personalised movie with your favourite virtual actors. Meanwhile, film companies may be able to avoid flops in the future: The storyline of a movie script will be analysed by sophisticated predictive computers, which will forecast its box office possibilities.

Medicine

Why would you want to take medicine that is beneficial for the ordinary individual when you could have it personalised to your specific genome? Doctors and hospitals will be able to more effectively evaluate data and tailor health care to each person’s genes, surroundings and lifestyle thanks to AI algorithms. AI will drive the personalised medicine revolution, from detecting brain tumours to determining which cancer treatment would work best for each individual.

Cybersecurity

In 2023, there were around 707 million cybersecurity vulnerabilities, with 554 million in the second quarter of 2023. Companies are fighting to keep one step ahead of cybercriminals. AI’s self-learning and automated skills, according to USC experts, can help consumers protect their data more consistently and inexpensively, keeping them safe from terrorism or even small-scale identity theft. Before harmful computer viruses and programmes can steal vast amounts of data or wreak chaos, AI-based techniques hunt for patterns linked with them.

Vital Tasks

AI assistance will help seniors maintain their independence and stay in their homes for extended periods of time. Artificial intelligence (AI) systems will ensure that healthy food is constantly available, that things on top shelves are safely reached, and that movement in a senior’s home is tracked. Many other repetitious and physical jobs are ideal candidates for AI-based technologies. However, in dangerous fields such as mining, firefighting, mine clearance and handling radioactive substances, AI-assisted employment may be even more vital.

Transportation

Self-driving cars are one area where AI may have the greatest impact in the near future. AI drivers, unlike people, never give up at the radio, apply mascara, or squabble with their children in the backseat. In European cities, self-driving trains have already taken over the rails, and Boeing is developing an autonomous airliner.

List of Jobs Where AI Will Take Over Customer Service Executives

To do their tasks, customer service agents wouldn’t need a high level of social or emotional intelligence. Many organisations increasingly rely on AI to answer frequently asked questions and provide customer care. Chatbots are becoming more than just a part of customer support. They also respond to a variety of internal inquiries.

Bookkeeping and Data Entry Receptionists

In the long run, automated check-ins in both small and large motels will reduce the need for hotel staff. Customers can now place orders through communication displays or tabs in fast food places. There’s a good chance that, with AI, machines will be able to handle purchasing and other related activities.

Proofreading

While editing is more difficult in terms of tone, comprehension, and other factors, proofreading is a much easier task. Different applications can easily detect grammar errors, sentence construction mistakes, and other mistakes. Grammarly, for instance, is one of the most well-known programs for this purpose among professionals.

Retail Services

People who handle sales have been replaced by automated services. Many merchants are focusing on self-ordering and payment methods, and AI can be incorporated fast. In order to truly comprehend client habits, many retail professions are being substituted by robots. Furthermore, the substantial data analysis performed by AI machines reveals alternative products that customers may be interested in in the future.

Courier Services

As a wake of AI, the shipping sector has undergone various social and economic changes. Several logistics and supply chain operations have been streamlined. As deliveries, drones and robots are already substituting people. Robotic automation will have the biggest effect on the shipping industry in the future years, aside from the manufacturing industry.

Military

Military experts believe that future battlefields will be populated by robots capable of following orders without continual monitoring. Robots are utilised extensively in military operations for a variety of functions including surveillance, data and many more.

Taxi and Bus Drivers

This industry has a 97 % likelihood of being entirely automated. Self-driving cars are already on the market, and fully autonomous cars won’t be far behind.

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Salesforce Ai: The Future Of Sales Automation

Introduction

Salesforce is the world’s leading Customer Relationship Management (CRM) software, providing businesses with a platform to manage their customer interactions and streamline their sales process. In recent years, Salesforce has been at the forefront of the integration of Artificial Intelligence (AI) into its platform. Salesforce AI is the future of sales automation, and it is changing the way businesses approach sales.

Section 1: What is Salesforce AI?

Salesforce AI is a suite of artificial intelligence technologies integrated into the Salesforce platform. Salesforce AI includes a range of features, including predictive analytics, natural language processing, and machine learning algorithms. These features work together to help businesses automate and optimize their sales process, from lead generation to customer retention.

Salesforce AI is built on the Salesforce Einstein platform, which is designed to enable developers and businesses to build AI-powered applications. Salesforce Einstein is a powerful tool that provides businesses with the ability to automate and optimize their sales process using AI and machine learning.

Section 2: AI-powered Sales Automation Features

Salesforce AI includes a range of AI-powered features that can help businesses automate and optimize their sales process. In this section, we will discuss some of the key features of Salesforce AI and how they can benefit businesses.

Lead Scoring Opportunity Scoring

Salesforce AI uses machine learning algorithms to analyse a range of data points to assign a score to an opportunity. These data points can include the opportunity’s stage in the sales pipeline, the engagement of the customer with the business, and the deal size. By analyzing these data points, Salesforce AI can provide businesses with a clear understanding of which opportunities are most likely to close, allowing them to prioritize their sales efforts.

Predictive Analytics

Predictive analytics is the process of using data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. Predictive analytics can be used to identify trends, forecast outcomes, and identify potential risks.

Natural Language Processing

Salesforce AI includes a range of NLP tools, including sentiment analysis and chatbots. Sentiment analysis can be used to analyse customer feedback, reviews, and social media posts to understand how customers feel about a business. Chatbots, on the other hand, can be used to automate customer interactions, providing customers with quick and easy responses to their queries.

Automated Email Campaigns

Automated email campaigns allow businesses to send targeted and personalized emails to their customers, based on their behaviour and engagement with the business.

Salesforce AI includes a range of tools to help businesses automate their email campaigns. These tools can be used to send targeted and personalized emails to customers at the right time, helping businesses increase their conversion rates and sales.

Sales Forecasting

Salesforce AI includes a range of sales forecasting tools, including predictive forecasting and opportunity tracking. These tools allow businesses to gain insights into future sales trends, allowing them to make informed decisions about their sales strategy.

Section 3: Benefits of Using Salesforce AI

There are many benefits to using Salesforce AI in sales automation. In this section, we will discuss some of the key benefits of using Salesforce AI.

Improved Efficiency

Salesforce AI can help businesses automate and optimize their sales process, reducing the amount of time and effort required to close deals. By automating tasks such as lead scoring and email campaigns, businesses can focus their efforts on high-priority tasks, increasing their efficiency and productivity.

Increased Sales Improved Customer Experience

Salesforce AI can help businesses improve their customer experience by providing personalized and targeted interactions. By using NLP and chatbots, businesses can provide quick and easy responses to customer queries, increasing customer satisfaction and loyalty.

Better Sales Forecasting

By using predictive forecasting and opportunity tracking, businesses can plan and allocate resources effectively, reducing the risk of over- or under-investment.

Competitive Advantage Section 4: Challenges of Implementing Salesforce AI

While there are many benefits to using Salesforce AI in sales automation, there are also challenges businesses may face when implementing this technology. In this section, we will discuss some of the key challenges of implementing Salesforce AI.

Data Quality

Salesforce AI relies on high-quality data to provide accurate insights and predictions. Poor data quality can lead to inaccurate predictions and insights, reducing the effectiveness of Salesforce AI. To overcome this challenge, businesses need to ensure their data is clean, accurate, and up-to-date.

Integration

Salesforce AI requires integration with other systems and technologies to work effectively. Integrating Salesforce AI with existing systems and technologies can be challenging, and businesses may need to invest in additional resources and expertise to ensure a seamless integration.

Cost

Implementing Salesforce AI can be expensive, and businesses may need to invest in additional resources and expertise to implement and maintain this technology. This can be a significant barrier for small and medium-sized businesses, who may not have the resources to invest in Salesforce AI.

Employee Training

Implementing Salesforce AI requires employee training to ensure they can effectively use and integrate the technology into their sales process. This can be time-consuming and expensive, and businesses need to ensure they have the resources to provide adequate training to their employees.

Security and Privacy

Salesforce AI relies on sensitive customer data to provide insights and predictions. Ensuring the security and privacy of this data is crucial, and businesses need to ensure they have adequate security measures in place to protect this data.

Section 5: Future of Salesforce AI

Salesforce AI is still a relatively new technology, but its potential for sales automation is vast. In this section, we will discuss some of the future developments and trends of Salesforce AI.

More Advanced Predictive Analytics Improved Integration with Other Technologies

As mentioned earlier, integration is crucial for the effectiveness of Salesforce AI. We can expect improved integration capabilities with other technologies, making it easier for businesses to integrate Salesforce AI into their existing systems.

Increased Personalization

Personalization is becoming increasingly important for customer satisfaction and loyalty. We can expect Salesforce AI to become even more personalized, providing targeted and personalized interactions with customers based on their preferences and behaviour.

Improved Natural Language Processing

NLP is crucial for automating customer interactions, and we can expect Salesforce AI to continue to improve its NLP capabilities. This will enable even more efficient and effective customer interactions, leading to increased customer satisfaction and loyalty.

Greater Adoption of Salesforce AI

Arguments Over The Future Of Openoffice.org

Don’t expect Oracle’s donation of the code of chúng tôi to The Apache Software Foundation to settle anything about the troubled office suite. If the situation does improve, it will be small thanks to Oracle.

According to Oracle, the donation is proof that “Oracle continues to demonstrate its commitment to the developer and open source communities. Donating chúng tôi to Apache gives this popular consumer software a mature, open, and well established infrastructure to continue well into the future.”

However, from the way that the donation was done, and the situation it leaves the project in, it looks very much like a last spiteful gesture toward the rival Document Foundation, the project that develops LibreOffice, the chúng tôi fork. The result is a future that leaves the future as troubled as the present. At the very least, to some observers it appears to show a disdain for the community that borders on arrogance.

If that sounds like an over-statement, consider the history. Some of the chúng tôi project members were dissatisfied for years with Sun Microsystem’s stewardship. When Oracle acquired Sun and its assets in early 2010, the dissatisfaction intensified. Many people pointed to Oracle’s lackluster treatment of other free software projects as an indication of what lay in OpenOffice.org’s future.

On 28 September, 2010, this dissatisfaction culminated in the creation of The Document Foundation. Organized by employees of Novell, Red Hat, and other corporations involved in chúng tôi The Document Foundation announced a fork called LibreOffice, and immediately attracted a large number of people who had previously worked on OpenOffice.org.

Although The Document Foundation invited Oracle to join its ranks, relations between chúng tôi and LibreOffice appeared to deteriorate when Oracle declared involvement in both projects a conflict of interest and insisted that LibreOffice supporters resign from their positions on the chúng tôi Community Council.

Almost immediately, The Document Foundation proved it had more momentum than chúng tôi with more discussion and proposals on its mailing lists. Within weeks, major distributions such as Ubuntu were deciding to ship with LibreOffice rather than OpenOffice.org.

Yet, despite such setbacks, Oracle’s previous assertion that it was committed to chúng tôi made most people believe that the rivalry would continue indefinitely.

At the time, the announcement was greeted with cautious optimism. But, since then, Oracle employees working on chúng tôi have been laid off, including long-time community manager Louis Suarez-Potts. Most of the project’s mailing lists shut down, and the last development patch was submitted on April 18. For all practical purposes, chúng tôi was dead, leaving dozens to wonder what was going on.

According to Steven J. Vaughan-Nichols, the donation to The Apache Foundation was made with the encouragement of IBM, which develops Lotus Symphony, another chúng tôi fork.

From a corporate viewpoint, you can imagine several reasons why the donation makes sense. As an umbrella organization of nearly one hundred projects, The Apache Foundation resembles a corporation more than most free and open source software (FOSS) organizations, no doubt making it easier for Oracle to deal with. It is also well-established and unlikely to disappear, so chúng tôi has a permanent home.

Furthermore, Vaughan-Nichols writes that Oracle is contractually obliged to IBM to ensure the continued development of chúng tôi If that is so, then you do not need to be a tactician to understand why Oracle might donate where IBM wanted it to. You might also view the donation as a peace offering after clashes with The Apache Foundation over various issues about Java.

As for the free office suite community, donating to Apache at least superficially satisfies requests that the code be turned over to a neutral, FOSS-friendly organization. Until yesterday, the community was planning to petition Oracle to donate the code (I know, because I drafted the petition), but the donation suddenly makes the effort moot.

Even The Document Foundation officially announced that “we welcome Oracle’s donation of code that has previously been proprietary to the Apache Software Foundation.” Superficially, at least, everyone sounds pleased about the donation.

So why is the donation less than ideal? One answer is that The Apache Foundation has more experience with projects that involve servers and infrastructure than desktop appliances. If chúng tôi is going to thrive, then the Foundation needs to learn, and quickly.

Another reason is that the donation means that most of the chúng tôi code is now licensed under the Apache License, rather than the previous GNU Lesser General Public License (LGPL). That means that some parts of the existing code are now incompatible with the main license, and may need to be discarded or rewritten.

The difference in licenses also reflects a difference in FOSS cultures, since the Apache License does not prevent the code being used under a proprietary license. For at least some of the OpenOffice.org-LibreOffice community, this license is likely to be objectionable.

However, by far the largest problem is that what the Apache Foundation has been passed is a project with few, if any members. This leaves the situation much as it was with Oracle, with official title to the code controlled by one organization, and most of the development and innovation being done by another — The Document Foundation.

What makes this development especially unfortunate is that, in the last couple weeks, the members of this joint community have been edging towards reunification.

The mutual distrust between Oracle and The Document Foundation, it appears, was largely on the organizational level. In the community, working relationships seem to have been at least partly preserved.

For example, Louis Suarez-Potts went out of his way to point out that he and Florian Effenberger, a member of The Document Foundation’s Steering Committee, work for the same company and have “sought to maintain cordial and even friendly relations since last year.” Similarly, Charles-H. Schulz, another member of The Document Foundation’s steering committee, emphasizes that “We have here one community and two projects.”

True, the Document Foundation has indicated a willingness to work with the Apache Foundation, and states that it has received an email from Jim Jagielski, “who is anticipating frequent contacts between the Apache Software Foundation and The Document Foundation over the next few months.” So there is at least the possibility of a diplomatic reunification occurring in the near future.

But, for now, the community’s efforts, if not its individuals, remain divided in a way that is harmful to all parties. Schultz tells me that a project on the scale of chúng tôi under Sun requires ten million Euros a year. Alternatively, it needs to mobilize volunteer contributors on a massive scale. Yet, even if Apache can find the cash or volunteers, that still means a duplication of efforts that is wasteful and inefficient.

Furthermore, Schultz argues, reunification can only serve the greater good. It would restore confidence among corporate and private users, and remove any uncertainty about Open Document Format, the ISO standard for office files that both LibreOffice and chúng tôi offer as an alternative to Microsoft Office’s file formats.

Still another problem is branding. Although chúng tôi was not as well known as proprietary rivals such as Microsoft Office, over the course of ten years it had developed a certain name recognition. By contrast, in the seven months of its existence, LibreOffice has yet to achieve comparable recognition. In fact, as a new brand, LibreOffice is sometimes regarded with suspicion by users outside the free software community.

Specifically, Schulz argues for reunification under LibreOffice. His argument is that LibreOffice has already proven itself better able to attract community developers than chúng tôi ever was. “In seven months, we have attracted twenty times more developers than the chúng tôi project, [and] we have extended the number of contributors to a bigger size than the chúng tôi project ever had.” The strength of this argument only increases when you consider that the Apache version of chúng tôi will probably need a month or two to organize, assuming that it become a going concern in the first place.

After the animosity, expecting Oracle to donate anything to The Document Foundation is probably asking too much of human nature. All the same, reunification seems a sensible goal, even if not necessarily under The Document Foundation.

But instead of listening to the community, Oracle has chosen a solution that not only threatens to preserve the existing divisions, but also ignores the wishes of the community by making reunification more difficult. The unsettledness of the solution seems a direct contradiction of Oracle’s high-minded statements about supporting FOSS.

This story is unfolding rapidly. Rumors are that another twist or two are expected later this week. In addition, another petition is being contemplated by some members of the community — this time, to The Apache Foundation, requesting that it turn its new assets over to The Document Foundation.

Such a move may not be strictly necessary. It may be enough for Apache to show a willingness to cooperate by joining The Document Foundation. If that happens, efforts would still be duplicated when resources are scarce, but at least some degree of cooperation might happen in a way that was impossible under Oracle.

Maybe then chúng tôi could finally be free to become a true community project of the sort that many have dreamed about for years. After Sun’s and now Oracle’s mismanagement, such an outcome seems long overdue. Let’s hope that Apache shows a greater concern for contributors and users than its predecessors.

Mark Montgomery: Impeccably Changing The Ai Landscapes With Over Two Decades Of Expertise

Experimenting with Technologies and Firms

In 1995 Mark founded the knowledge systems lab as a small business network, and in 1997 he launched GWIN, which was a cutting-edge social/learning network. “I ran the lab solo from our property in rural Arizona. The idea for KYield came to me while operating GWIN almost 25 years ago now”, says Mark. But soon he realized that it would take at least a decade before the technology would be viable and during that time, Mark incubated KYield while running an early-stage VC firm. In 2006 he filed a patent application covering a portion of KOS which is what we today call the distributed AI OS. He states that the AI systems patent wasn’t approved until 2011. Meanwhile, in 2010, he announced his healthcare platform, and in 2012 Mark tested the basic data structure with a mutual vendor on one of the largest financial networks. “From 2009-2023 I was also a frequent guest at the Santa Fe Institute. I’ve engaged with senior management in many of the world’s leading organizations over the last decade”, adds Mark.

AI Systems that Taught Hard Lessons

Mark mentions the hard lessons he learned during his journey from the idea to the commercialization of large-scale AI systems. He says that those experiences were the reasons which profoundly shaped him. As running the early lab and networks is critically important, he notes that Les Vadasz,

The Two Attributes for Success

Firstly, Mark says that he didn’t set out to become a leader or an influencer in AI. The most important part he believes is to invest time is to understand the science, engineering, operational, and business environments, without which he affirms to have no credibility. To become competent in AI systems, he presumes that it requires consuming tens of thousands of papers across several disciplines, including computer science, mathematics, and physics, though he also recommends economics, neuroscience, and psychology. Secondly, he stresses upon getting some good hands-on experience in an applied lab. He firmly trusts that when an individual can demonstrate rightly, they are capable of understanding science and engineering better to forge new ground, that’s when he says one can become an influencer.

Fostering Innovation to Stay Ahead

“We’ve had a great many direct discussions along the way of course, but when we first approached senior management teams in the world’s leading organizations, not a single one had ever considered the concept of enterprise-wide AI systems”, says Mark. He feels that his experience has been a bit like that expressed by Steve Jobs – “Our task is to read things that are not yet on the page”. Now, Mark takes pride in saying that the KYield is attempting to remain many years ahead of the herd. Mark strongly affirms that disruptive aspects of the technologies are just beginning to have an impact on healthcare, education, and government, which are resistant to change yet also the sectors society needs to change the most due to economics and need. He says that we are already at the stage where CEOs of most organizations should be well along in the process of becoming experts in AI systems. Otherwise, he believes that they won’t be able to even recognize whether ana device is good or bad and it may turn out to be one of the greatest problems that business nations would face.

Embracing the Challenges Optimistically

The first decade of KYield was devoted primarily to theoretical research and technical viability and Mark on the other hand didn’t formalize the underlying mathematical theorem until a few years ago. After which he met with a CEO of a leading tech company in 2007 and had some partnership talks and his scientific fellows reported that KYield was impossible. Though it wasn’t impossible, Mark thought the CEO understood it. Mark’s commercialization journey began after the initial patent was approved and data structure got tested. KYield was initially limited to organizations that had a supercomputer, but in 2010, he estimated the cost of a primitive pilot to be about US$100 million. Even though he didn’t sell any, most showed a high-level interest in buying it. When the AI revolution really began to take off in 2014 followed by tens of billions of dollars of investment, there was an increase in performance which led to the reduced cost for his KOS by more than a factor of 10. Mark says that KYield has come a long way in the 25 years since the idea stage. And he also wrote an article on the recently for those seeking more detail.

A Future Representing SGM

In this context, Mark talks about his most recent invention called the synthetic genius machine (SGM), by reflecting much of the last decade in R&D at KYield. He thinks the SGM represents the future quite well as it will provide the narrow superintelligence as a service at the confluence of data physics, AI, and quantum computing. Through this, his primary value to society will be accelerated discovery, research, and development.

Words of Wisdom to the Buds

The Future Of Wedding Rings In Collaboration With Technology

Three decades ago, the world was without the internet, and so much of the comfort technology brings.

But now, technology has touched almost all aspects of human lives, and it is not surprising that rings are soon to be adopted into new digital technologies and modernism.

Rings are no longer limited to gold, titanium, or diamond-plated rings; here are other technological inventions that will be incorporated into the future of rings.

Bitcoin Rings

It is not a surprise that this is a suggestion as it is obvious that BTC will be a part of the future, so why not have something different and unique, like a BTC ring?

This suggestion was brought up by Inventor Seb Neumayer, who suggested a BTC ring to replace a physical one.

This unassuming bit of metal is 3D printed, programmable, and has a QR code that connects to the Bitcoin blockchain. Anyone using the relevant software can scan the ring to find out its value.

Neumayer believes traditional engagement rings are already a sign of wealth, so why not make the entire process completely transparent?

The main intention is to devalue the actual ring, which is easily lost or stolen. Nobody is likely to want a QR code glued to a metal band; even if they did steal it, the ring does not carry a password to access the linked funds. Carrying a big rock around might leave you vulnerable to mugging.

NFT Rings

If there can be a bitcoin ring, nothing is stopping the invention of an NFT ring. And anyone who would like the idea of a Bitcoin ring would also buy an NFT ring.

You simply buy rings in the digital space the same way you would purchase a work of art.

Anticipating The Birth Of Ai Employee Clones

I was in New York recently attending two overlapping events: the Lenovo Advisory Council and BlackBerry’s Security Summit. I have no doubt I am not alone in having to be multiple places at once.

We not only have to balance often conflicting business schedules but conflicting life schedules. We have children, spouses, friends, and hobbies along with our work, and we all realize this is not necessarily conducive to creating the right work-life balance.

These conflicts force us to make hard choices that we often regret as we approach the end of our lives. This has certainly happened to me. We might not have been there to support a child, spouse, friend or coworker when they most needed us. Because we prioritized something tactically, like attending a critical meeting, and forgot that often it is our more strategic relationships that should have had priority. Thus, our relationships with family and friends have been weakened, particularly our relationships with our children.

There is a coming AI technology that, assuming we use it correctly, could make this problem obsolete. That technology is human AI clones or human digital twins. I am using the term human AI clone, because it better reflects what is coming and better focuses on both the promise and the problem with the technology. I will cover both the promise and the problem. But I would like to set the promise of the technology as the goal — and start having people think about how this technology should be used before we find it has been deployed badly.

Let’s begin.

The promise of AI employee clones or human digital twins

The idea of creating an AI-driven clone of a person is far from new. It is at the heart of digital immortality, and it will also be critical for the creation of large-scale environmental simulations, be they focused on industry or entertainment. On the latter, the concept of realistic non-player characters (NPCs) would be a game-changer. But the true benefit to us individually is that we can delegate an increasing portion of our lives to the clone.

How much do you contribute to a meeting? That depends on the meeting. In large meetings designed to provide updates, we are often merely observers and provide no additional value. In other meetings, we may ask one or two questions, and on way too many occasions, we find we did not even need to be there. However, we seldom know this critical piece of information until we are in the meeting and see the content. Virtually no meeting leaders send their content out before the meeting. Often, even a full agenda is the exception rather than the rule.

One fix is to demand better meeting preparation. But we’ve been pushing for better meeting preparation for as long as I have been in business, and we just have not made that much progress. Granted, it could be because too many people wait until the last minute to work on their content. But if we can’t fix this problem one way, we can use technology to fix it another way. That problem is that our time is a limited resource, and we need better ways to focus that limited resource where it can be most effectively used.

See more: The Top Artificial Intelligence Companies

Preventing replacement

The problem is where I fear this technology will be focused, which is employee replacement. That would be a bad outcome: because it would cause employees to fail to train their clones; and because it would feed into too many executives’ belief that companies would run better if they could just eliminate their employees.

These human AI clones need to be owned by the employees that create them, and if they are used after the employee leaves the company, the employee should continue to be compensated. This could flow into their eventual retirement, creating a stronger reason to invest the time into creating that tool.

Assuring this technology benefits rather than harms the employee is critical to assure that it will both do what it will be able to do and drive the huge potential work-life and productivity benefits it can provide.

See more: AI, Automation, & the Future Impact on Jobs

What side is the money on?

The promise of employee clones is significant. It could mean more time spent on things we love to do at work and far less on things that waste our time and annoy us while improving work-life balance and helping to fund our retirement.

The problem will be the desire for companies to own the resulting clones and use them to replace their employees. Sadly, the money is on the wrong side of this, and our goal is to assure that this money dynamic does not drive the wrong outcome.

See more: Artificial Intelligence Trends & Predictions

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