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Artificial Intelligence

Artificial Intelligence

AI and Customer Service: How Chatbots and Virtual Assistants Are Changing the Industry

by Najam on
ai

Artificial intelligence developments are fundamentally altering company models, and chatbots are gradually taking on increasing importance in customer support channels. A.I. and machine learning make recognizing the substance of client requests, queries, and service inquiries possible. Chatbots continue to gain in popularity as messaging applications overtake social media networks in terms of use.

A company must adjust to the requirements and desires of its customers before using more effective methods to serve them. By allowing consumers to contact the business through messaging apps, email, or SMS, chatbots are transforming how businesses interact with their clients and fostering brand loyalty.

Customer Service Chatbots

A single bad customer service encounter might turn off potential clients. According to research by Business Insider Intelligence, 60% of U.S. shoppers have abandoned an intended purchase because of lousy customer service, which may cost U.S. retailers billions of dollars in lost sales.

Online customer service has improved users’ propensity to connect with firms electronically since customers have many alternatives. A 24/7 chatbot that handles customer care is a solid and affordable approach to providing customers with basic help since convenience is a crucial part of the customer experience.

Customers should get the same quality of assistance as they would from a representative. Still, if a problem becomes too complicated, the client may be sent to a natural person. Chatbots used for customer service often respond to questions using keywords. Chatbots can now ask questions, provide context and intent, and provide better customer service thanks to advances in AI.

Chatbots For Virtual Assistants

A virtual assistant chatbot (VAC) and a customer service chatbot (CSR) have different purposes. Its core technology is comparable otherwise. Virtual assistant chatbots (VACs) help with business, education, government, healthcare, and entertainment applications by giving information, services, and help with websites.

Specific virtual assistants are utilized to assist company personnel than clients outside the company. VACs may do various actions to help organize an office, like making lists, setting reminders or appointments, launching the software, or turning on intelligent devices. They may all be managed via text or voice commands.

What Use Does Artificial Intelligence Play in Customer Support?

A smooth, customized customer journey is created using artificial intelligence (AI) technology, starting with a prospect’s first web search and continuing through your follow-up marketing, the first sale, and all subsequent interactions. You integrate and utilize all the behavioral data you’ve gathered along the route to reduce friction at every touchpoint.

Your buyer’s journey is one of many aspects of an intelligent customer experience that is made more accessible. It also helps your team work better and faster thanks to intelligent routing, insights from AI, and prompts, as well as chatbots and voice assistants that make the work easier.

The Importance of Customer Experience

If a consumer has a positive experience with your business, you will likely gain their repeat business and maybe even their recommendations. But, this will only happen if you continue to engage with them and provide consistently top-notch service.

Certain Ways AI Enhances Customer Experience

The usage of AI in businesses has grown significantly in recent years. According to the Big Data and AI CEO Survey 2021 by NewVantage Partners, 77% of respondents use AI in some capacity, and 96% of them report that it has helped them achieve successful results, an increase of 25% from 2020. Your company benefits in a number of ways when you create an AI customer experience:

Save clients’ time and money.

The consumer experience is improved via chatbots, virtual assistants, and in-app communications APIs. According to our most recent Global Consumer Engagement Study, AI can help companies provide more satisfying customer experiences.

Engage Clients With Fresh Sales Chances

By providing individualized product suggestions and exclusive deals, AI may encourage more purchases. Based on previous purchases, it may inform clients when it’s time to place another order.

Boost the retention of customers

According to the Global Customer Engagement Report 2022, 53% of consumers will increase their loyalty to a company after a positive customer experience. Similarly, 36% of buyers anticipate making more purchases.

Boost personnel productivity

AI frees up human agents to concentrate on their core strengths and insights that help them perform more effectively by intelligently routing consumers, qualifying sales leads, and unloading customer support responsibilities.

Decide Based on Data to Enhance Client Experience

The customer experience is being improved by your AI-powered solutions, but they are also collecting and analyzing data that might help you better understand the customer journey and spot pain areas that can result in customer turnover.

Which AI customer experience solutions are the most valuable?

Virtual Helpers

AI-driven virtual assistants can replace phone trees with conversational, intelligent routing, so clients don’t have to listen and reply to lists of alternatives to (hopefully) reach the proper agent. Instead, users just state their needs to the virtual assistant, and AI connects them to the proper person using that information and customer history data. The virtual assistant may also give easy answers, help, and even finish transactions based on your integrations.

Chatbots

Chatbots are like virtual assistants. They may provide information, respond to queries, and allow self-service. By adding them to your website, app, and social media channels, customers can talk to your brand anytime and get quick answers to their questions without leaving your content or product listings.

Hence, take into account including chatbots in:

Get rid of wait times: AI-powered chatbots may assist in reducing hold times, especially for frequent queries.

Establish 24-hour sales and customer service: Chatbots anticipate queries and provide suitable products and alternative suggestions. Consider it a step forward to offer shipping information, check stock, size, or color, or direct them to a tailored in-store visit. The ongoing in-channel interaction may support clients through the buying cycle.

Sentiment Assessment

Sentimental evaluation A customer’s emotions may be seen in real-time thanks to AI bots that listen in on discussions. This may let you know when they’re interested or irritated. During interactions with a chatbot or virtual assistant, if the AI senses that the person is getting more annoyed, it may call a human right away. Also, it might include a knowledgeable supervisor if clients are dissatisfied with the agent’s service. Vonage’s Sentiment Analysis solution also gives managers the information they can use to teach their teams better and improve the customer experience. It also gives agents clear, real-time feedback to help them improve their skills.

Language Recognition

Speech synthesis AI takes advantage of natural language processing to comprehend clients’ needs and provide conversational responses. It drives everything, including IVR, chatbots, virtual helpers, and call transcription. Speech recognition can be used to make sure a customer is who they say they are and to give them access to their account information and self-service options.

Use AI in your company to begin seeing results.

A short while ago, big tech businesses with significant expenditures were the only ones using AI. It now powers all the services and applications we use daily. All organizations can provide an AI customer experience, but different enterprises have different use cases.

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Artificial Intelligence

AI and Law: The Intersection of Intelligent Machines and Legal Practic

by Najam on
ai

Artificial intelligence (AI) is a technology that is increasingly being used in both our personal and professional lives to make things easier and more convenient for us. Whether you know it or not, AI influences your daily life. ChatGPT, the live chat feature on your favorite e-commerce site, face recognition to unlock your phone, and the estimated time your Uber will arrive are all examples. 

Even though many industries are just starting to use AI, its effects can already be seen in manufacturing, sales and marketing (using chatbots like ChatGPT), accounting, human resources (using automated applicant screening), and inventory management.

Even though the legal field has been slow to adopt new technologies in the past, AI is starting to have an effect on law firms. By automating routine tasks like document management, billing, and legal research and analysis, AI in law firms could make your business much more productive and save you a lot of money. Let’s look at what AI is and how it might benefit your legal company.

Artificial intelligence: What is it?

A machine that has been trained to carry out one or more human functions is referred to as having artificial intelligence (AI). For instance, set a reminder on your smartphone to contact your buddy Alex at 5:00 p.m. every Wednesday. And unless you instruct your smartphone to stop sending reminders, you’ll get one every Wednesday. 

Another term you may be familiar with is “machine learning.” “Artificial intelligence” and “machine learning” are sometimes used interchangeably, but they mean two different things.

Will AI take the place of attorneys?

Without a doubt, AI technologies provide prospects for attorneys. Automation lets lawyers spend less time on tasks that don’t bring in money and more time helping clients.

Legal practitioners should be aware of some of the issues that AI presents. While adopting AI technology, attorneys must be aware of their ethical responsibilities.

AI may help automate processes, save attorneys time, and even make their legal writing more interesting, but it’s not meant to replace people who work. Also, being afraid of technology can stop you from helping even more customers, even though it might save you and your business time.

AI vs. machine learning

AI includes machine learning as a subset. It alludes to the process through which people teach computers to learn from data input. Machine learning searches for patterns in data to make inferences as opposed to just carrying out (or duplicating) a human activity. After the algorithm has figured out how to get one accurate conclusion, it may then apply those findings to fresh data.

How can attorneys in law firms utilize AI?

AI is presently used extensively in the legal sector. While it may not be immediately apparent, artificial intelligence in law companies improves how well paralegals and attorneys do their duties. In particular, AI in law companies assists legal practitioners in changing their practice by putting clients first in a previously unheard-of manner. These are just a few ways that law firms might benefit from artificial intelligence in their operations.

E-Discovery

The simplest and most well-liked sort of AI in law is e-discovery, which is the act of searching electronic material for non-privileged information that is pertinent to a case or claim. Lawyers can search documents using search terms or specific criteria like dates or locations by using e-discovery software. 

So, lawyers get answers almost right away, which is a lot faster than scanning paper documents. This additional time enables attorneys to find more pertinent information.

Legal Analysis

Similar to e-discovery software, legal professionals can quickly scan and search huge databases of rules, laws, practice areas, jurisdictions, case laws, and more using AI-powered legal research software. Legal research software allows professionals to gather information and understand precedents. 

Management And Automation Of Documents

The challenges of electronic document storage are similar to those of hard copy document storage as law firms continue to move away from paper documents. Even though electronic records require less physical space, sorting and finding documents is still difficult.

AI-driven document management software saves and arranges legal documents, such as contracts, case files, notes, emails, etc., using tagging and profiling features. Finding documents is much simpler with this approach of storing and organizing digital files and full-text searches.

Diligent Effort

Legal experts often need to analyze a significant number of papers, including contracts, as part of due diligence procedures. Similar to other document-related issues, AI may speed up the document review process for legal practitioners. 

What’s best? AI can quickly review papers. Although a human evaluation of the material is still advised, attorneys might gain by dramatically lowering the manual work involved in document assessment.

Legal evaluation

It takes a thorough examination of precedent-setting decisions to determine whether a lawsuit is likely to succeed or to calculate its worth. These precedents may be promptly reviewed by lawyer AI, which can then be used to assist attorneys to create more accurate and relevant papers.

How can legal AI help the client and the firm?

The use of AI in law businesses improves the productivity of legal experts. Overall, AI helps decrease the amount of time spent on manual chores, giving up more time to invest in activities that concentrate on developing relationships with clients. Many advantages exist for both clients and the bottom line for law firms:

Increasing Output

Automation of repetitive manual operations with AI increases productivity across the company. To increase efficiency, AI-driven procedures take the place of labor-intensive, time-consuming tasks including contract research, due diligence, and invoice creation. 

Lawyers may spend more time on their clients while increasing the amount of billable work they do when they become more efficient.

Increasing Justice Access

Machine learning and artificial intelligence have the potential to lower obstacles to justice, most notably the high expense of hiring an attorney. Lawyers may lower estimates and expenses for clients by spending less time on manual and routine legal work. 

For instance, if the research that used to take 20 hours now only takes two, attorneys may pass those savings forward to their clients. Also, by saving time on laborious research, attorneys may use that time to help additional clients. Although the potential for applying AI in the legal sector is present, it has not yet been completely realized.

Better customer-centered services 

Giving attorneys and other legal professionals more time is the key benefit of adopting artificial intelligence in law companies. AI-driven technologies that reduce labour and time requirements provide attorneys more time to interact directly with clients and build trust. 

Legal professionals should be able to do more than only assist clients with their legal problems. With additional time, attorneys may get to know their clients better and properly understand how and why they need legal counsel.

AI’s ethical implications for legal firms

Lawyer AI is a part of the complex and quickly changing field of technology, where new applications and discoveries happen almost every day. The entire effect or possible applications of such instruments are not yet completely understood. A cautious approach is ideal in a field like a law that is compliance-driven.

Model ABA Rules

The first rule of the American Bar Association deals with “competence” and an attorney’s duty to provide “competent counsel to a client.” In 2012, a note was added to the regulation saying that it is important to know “the benefits and risks of applicable technology” in order to be a good lawyer.

Unconscious bias

Implicit bias is one of the biggest concerns in machine learning and artificial intelligence. No matter how impartial we attempt to be, we are fundamentally biased since we make machines. 

According to data, face recognition software, for instance, has trouble correctly recognizing people who are female, black, and between the ages of 18 and 30. Many people think that this is because most of the early users and creators of the technology were white men. The disparity is concerning since law enforcement organizations often employ such technology to help identify criminal individuals.

AI tools for lawyers

In the meantime, lawyers may use a number of powerful AI-driven tools to help them do their jobs better and pay more attention to their clients’ needs. Below is a list of the best tools:

Smith.ai

Smith.ai uses AI to decide how to record and route calls and how to set up its chatbot capabilities. Clio is integrated with the receptionist and chat services.

Gideon

With a short talk, Gideon may fully replace lengthy, friction-heavy intake forms. Clio and Gideon work well together as well.

Casetext

Casetext also integrates with Clio, so legal professionals can conduct searches with one click, right within Clio, and save the results directly to the current matter.

Diligen

Diligen helps attorneys do their due diligence by using machine learning to look through contracts for certain clauses, conditions, or changes and quickly produce a useful summary.

Legal AI: Improving the client-centered process

The future of AI in law firms is still uncertain, but the legal sector has already reaped enormous advantages. Companies should use legal AI technologies if they want to be more efficient, make more money, pay more attention to their clients, and improve access to justice.

 

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Artificial Intelligence

Exploring the Latest Advances in Natural Language Processing with GPT-3

by Najam on
Natural Language Processing

Exploring artificial intelligence (AI) has a number of basic challenges, including natural language processing (NLP). In order for robots to connect with humans in a more organic and intuitive manner, they must be taught to comprehend and produce human language.

The development of machine learning and deep learning over time has greatly aided NLP. Neural network models that learn from a lot of text input have supplanted early efforts to codify grammar rules and lexicons. These models have developed through time, and now they are capable of carrying out a variety of natural language tasks, including as question-answering, text summarization, and language translation.

The state-of-the-art language processing model GPT-3 (Generative Pretrained Transformer 3), created by OpenAI, is one of the most recent and spectacular instances of this development. The AI community has paid close attention to GPT-3 because of its outstanding skills and enormous size (175 billion parameters).

As a sort of language model, GPT-3 is taught to anticipate the next word in a given string of text. As a result, it may produce cohesive language that flows naturally. GPT-3, however, is far more capable than merely text generation. Moreover, it is capable of carrying out a variety of natural language activities, including question-answering, summarizing, and translating.

The capacity of GPT-3 to adapt to new domains and tasks without the need for fine-tuning or retraining is one of its fundamental characteristics. This implies that it may be used to a wide range of applications, including sentiment analysis and chatbots as well as virtual assistants and content development.

Moreover, it has been shown that GPT-3 produces writing that is hard to tell from a text produced by a person. This makes it a useful tool for both corporations and organizations looking to automate language-based processes as well as scholars looking to study and comprehend the subtleties of human language.

Overall, GPT-3 marks a significant advancement in AI and natural language processing. It is a useful tool for both academics and developers because to its versatility and capacity to produce text that resembles human speech. We may anticipate seeing even more remarkable language models, like GPT-3, that can help us realize the full potential of human language as AI develops.

GPT-3 presents intriguing prospects for businesses in addition to its potential uses in research and development. Startups may use GPT-3 in the following ways to develop ground-breaking goods and services:

Virtual helpers:

GPT-3 can be used to make virtual assistants that can understand and answer questions in natural language. This could help a wide range of businesses, such as those in e-commerce, customer service, travel, and hospitality.

Creating content

GPT-3 has the ability to produce text that sounds like human speech, which may be helpful for businesses that need to produce a lot of material rapidly and effectively. For the purpose of creating articles, blog posts, and social media content, a company that operates a content marketing platform might use GPT-3.

GPT-3 can be used to figure out how people feel about the text, which could be helpful for businesses that want to track and understand how customers feel. For example, a company that runs a platform for customer feedback could use GPT-3 to automatically sort and rate user feedback.

Do you pass the Turing test?

What professions require taking one piece of text, altering it, and outputting a different piece of text? is one method to approach the question. stated Branwen. “Any position that fits that description—including medical coding, billing, receptionists, customer assistance, [and more]—would be a suitable candidate for fine-tuning GPT-3 on, and that individual would be a good target for replacement.” Many jobs involve “copying fields from one spreadsheet or PDF to another spreadsheet or PDF.” This kind of office automation is too disorganized to be easily replaced by a regular program, but GPT-3 could do it just as well as a human would.

Language conversion

Language translation can be done using GPT-3, which might be helpful for firms that operate in international marketplaces. GPT-3 could be used by a company that runs a website or app in more than one language to automatically translate user-generated content.

Final Verdict 

GPT-3 has a lot of possibilities for entrepreneurs who want to use AI to create new products and services. Startups may fully use the power of human language by using this cutting-edge language model, and they can provide their clients with brand-new and thrilling experiences.

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Artificial Intelligence

Optimizing Your Business with Artificial Intelligence: Best Practices and Benefits

by Najam on
Artificial Intelligence

Nowadays, artificial intelligence is a trending topic. Artificial intelligence is no longer simply a sci-fi notion reserved for Hollywood blockbusters; in recent years, it has emerged as a popular issue with several practical applications.

You may have read or heard about the ChatGPT bot, an AI-generated art platform called Dall-E, or how it can have real conversations and write song lyrics in the manner of your favorite bands. Nevertheless, with all the discussions about AI’s future that occur every day, it’s easy to forget about the smaller-scale ways that AI might help your company.

Every organization wants you to keep looking for opportunities to step away from routine chores so you can concentrate on the more important ones. See it as the evolution from the worker to the independent contractor to the AI: increased productivity, simplified daily activities, and strategic thinking. What level of dedication is expected of you as a company owner, and how might AI assist you?

What is artificial intelligence (AI)?

According to its definition, artificial intelligence is “the theory and development of computer systems able to do activities that typically require human intellect.” There are several levels of sophistication, from being able to do simple administrative chores to drawing valid judgments about intricate ideas.

Machine learning is a subfield of artificial intelligence that deals with specially trained computers that can keep becoming smarter the more data they analyze on their own. AI for the goal of increased human effect has been used by my own firm in the healthcare sector, which has been crucial in guaranteeing the most customized service to match individual demands.

Use of AI

Apart from industry-specific uses, the majority of us currently make use of AI in some way in our everyday lives, whether it is via Google searches, predictive text, or suggested playlists on music streaming services. But, the discussion around more sophisticated applications like face recognition and self-driving automobiles is likewise becoming more and more influenced by AI. Yet a lot of us are unaware that AI is more widely used in the workplace than you may imagine — and not in a scary, post-apocalyptic sense.

Service to customers and success

Customer service has always been and always will be king, which is an unchanging reality. The need for a personal, human touch cannot be emphasized, but AI may make a significant contribution to bettering customer service in general.

It may primarily assist personnel in handling fewer queries and streamlining processes. A chatbot, an automated messaging service that may assist with things like shipment updates, order timeframes, and product information, is often used by companies as the initial point of contact for any queries. It may be configured to respond to simple questions or customize user information and incorporated into a variety of businesses. They can even react in many languages, expanding your customer care options internationally.

AI may be helpful when it comes to customer success, which is the proactive effort done with clients to guarantee their contentment and retention of services. Instead than taking the place of a customer care representative, AI may gather vital data that helps to tailor the client experience. AI can utilize data to generate forecasts, pinpoint problem areas, and even suggest future service developments by providing 360-degree insight. Everything is done to maintain the customer’s satisfaction.

Replacing email correspondence

Even the most well-organized teams may fall apart rapidly when they get a large number of client emails where you have to keep track of purchases, inquiries, tracking numbers, and many other things. In addition to being logistically difficult, managing so many microtasks correctly and swiftly may also be irritating for the consumer.

An email bot, on the other hand, may automate the whole customer support process. It may do things like react to inquiries about price, provide updates on the status of orders, or refer more complicated issues to your staff. Some bots can even detect language and tone to avoid aggravating the situation by responding in a too-upbeat manner. This reduces the amount of time customer service representatives must spend responding to routine inquiries that can be answered automatically.

Promotion and sales

Have you ever considered where your firm would be now if you didn’t spend so much time on administrative tasks? AI has several uses in the marketing industry, where innovation is valued yet email overload is a common problem.

The main advantage is that because AI interaction and decision-making are based on factual facts like prior usage, historical purchases, and surveys, programs are able to get sales insights that a person could never have. Lead generation and lead scoring may be aided by this before choosing the best marketing approach. According to a report, 61% of sales teams that used automation in the sales process outperformed their revenue targets.

Writing blogs and SEO

By now, everyone is aware that helping artificial intelligence optimization and blog posts for SEO is a science that is ever-evolving. AI tools are becoming more sophisticated and capable of producing clear, factually accurate, and lively copy for your business.

One of the most difficult aspects of blogging is consistency, but AI can help you produce more because it can write and edit posts much faster. The marketing team can refine, supplement, and polish off strong copy frameworks for ads, marketing emails, social media copy, and explainers by simply entering keywords and a brief.

While AI hasn’t fully replaced employment (yet), it may certainly make our duties at work much simpler. It allows businesses to stop checking emails and start thinking forward by giving them more time for innovation, strategy, and long-term planning.

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Artificial Intelligence

The Promise and Pitfalls of AI in Education: Applications, Challenges, and Opportunities

by Najam on
ai

Technology permeates most fields. AI can significantly help education. Several colleges and academics have resisted AI. The leading cause is ignorance about AI’s benefits to education. As AI technology advances, it might change how kids and teachers learn. To use AI technologies that work, educators must plan a digital revolution.

Educational AI Grading software

AI-powered grading software uses Machinemachine Llearningearning to calculate assignment teacher- or s from teacher/professor-graded papers. The tools grading fromnstructors’ grading earlier.

They help instructors spend less time grading and more time on value-based work.

Administration

Automate scheduling, rescheduling, marking attendance, grading papers, financing, accounting, and record-keeping in schools, colleges, and universities. AI can do many things.

  • Preventing truancy
  • Report cards and other parent communication automatically
  • Arrange meetings
  • Accelerate progress reports.
  • Streamline other record-keeping.

It may let instructors and academics concentrate on instruction rather than paperwork and job pressure.

Assistants

Voice assistants make studying at home fun and easy by scheduling study calendars, listening to coaching instructions on the fly, and answering students’ fundamental inquiries in class. Voice assistants benefit education:

  • Students and instructors save time efficiently.
  • Community Education
  • Instantly personalizing education

Smartphone applications can employ AI-powered voice assistants without intelligent speakers.

Learner-centered

AI technologies may personalize learning with customized study plans. They find gaps in knowledge and fill them with training, testing, and feedback for students from preschool to college. AI-powered software, games, and tools may help students learn at their own pace and with repeated repetition. This machine-assisted classroom environment may help instructors adjust lesson plans to meet students’ requirements and promote differentiated and adaptable learning for all learners.

A customized learning system may notice that a student suffers from math. The plan would give the learner targeted practice problems or videos to help them understand. As the learner advances, the system adjusts education to fit their requirements.

Smart content

Creative content includes digital textbooks, manuals, instructional bits, videos, and AI systems that create personalized learning environments based on techniques and goals. Identifying where AI technologies might help personalize education is the next worldwide trend. 

Schools may build AR/VR learning environments and web-based curricula. AI monitoring and assessment technologies can adapt the information to various learning styles and paces. AI and ML-powered algorithms could find gaps in the curriculum and help teachers fix them when many students answer wrong.

Tutoring

AI-based tutoring applications may provide individualised feedback and directions for one-on-one training. They cannot replace teachers because they cannot teach. They may assist when human instructors are unavailable for short online classes. It may teach languages, geography, circuits, medical diagnostics, computer programming, mathematics, physics, genetics, chemistry, and more in e-learning platforms. They consider engagement, grading measures, and understanding.

e-Learning

VR lets students engage with information on their phones or computers. Virtual learning environments may include group instruction, student counseling, and immersive learning. VR headsets assist ADD/ADHD kids in focusing and filtering out distractions. Interactive virtual simulations also help learners acquire soft, life, and self-development skills.

Gamification

Points, medals, and leaderboards in AI-powered gamification make learning more fun. Gamification may engage pupils and teach critical thinking and problem-solving.

Gamification is employed in K–12, higher education, and professional training. In gamified math software, students get points for answeringansweringring practice questions correctly and advancing through levels as they understand various topics.

AI Challenges, and Opportunities

AI’s effects on learning outcomes, access to education, and teacher support are studied with the help of examples from China, Brazil, and South Africa. The challenges and opportunities  that are presented center on the following:

  • Establishing a thorough understanding of public policy about AI for sustainable development: The complicated technical requirements for advancement in this subject need the coordination of many entities and elements. National and international public policy must cooperate to build an AI ecosystem that supports sustainable growth.
  • With the development of AI, the least developed nations risk experiencing new technical, economic, and societal gaps. Particular significant challenges, including the fundamental technical infrastructure, must be overcome to create the actual circumstances for putting innovative tactics that use AI to enhance learning into practice.
  • To apply AI pedagogically and meaningfully, teachers must acquire new digital abilities, and AI developers must understand how instructors function to produce viable solutions in practical settings.
  • Data quality should be the key priority if the world is moving toward the ratification of education. To enhance data collecting and systematisation, state capabilities must be built. The growth of AI should give us a chance to make data a more significant part of how the education system is run.
  • Even though research on AI in education will grow in the coming years, it is crucial to remember how hard it has been for the education sector to use research effectively in both practice and policy-making.
  • AI raises several ethical questions about access to the educational system, personalized suggestions for each student, personal data concentration, responsibility, impact on the workplace, data privacy, and algorithm ownership. Public discourse on ethics, accountability, transparency and security will be necessary for AI legislation.

During Mobile Learning Week 2023, the main conversations will be about these topics. This is a rare chance for educators, governments, and other stakeholders worldwide to talk about the pros and cons of AI in all areas of education.

 

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Artificial Intelligence

The Dark Side Of AI: Examining The Risks And Limitations Of Intelligent Systems

by Najam on
ai

The Dark Faces of AI” special issue begins here. AI has enormous prospects to transform several businesses. This breakthrough technology allows driverless cars, face recognition payments, guided robots, and more.

AI is one of the top five developing technologies for digital-first organizations. Because AI technology is getting better and more available, 70% of businesses will build AI architectures by 2021. AI is inevitable. Several academics are now studying AI. According to research, AI has the potential to improve consumer interactions and boost corporate advantages (e.g., by increasing efficiency, increasing effectiveness, and decreasing cost).

The good things about AI get a lot of attention, but the bad things, especially in academia, don’t get much attention. Given AI’s relevance and universality, its negative effects on people, organizations, and society need more study. Considering the little study on the dark aspects of AI, we present this special issue and invite academics to examine crucial AI concerns, particularly in electronic market contexts such as electronic commerce, social media, emerging digital platforms, etc.

AI’s dangers have been questioned in tech. AI’s greatest risks are job automation, false news, and an AI-powered weapons race.

AI-Automation Job Losses

“This economy has made a lot of low-paying jobs in the service sector,” said futurist Martin Ford to Built In. “That won’t last.”

As AI robots become smarter and more agile, fewer people will do the same work. AI will generate 97 million new jobs by 2025, but if employers don’t upskill their workers, many may be left behind.

If you’re flipping burgers at McDonald’s and automation increases, would one of these new careers suit you? “Ford” “Or is it probable that the new career demands loads of schooling or training or maybe even inherent talents—really great interpersonal skills or creativity—that you may not have? Because computers are bad at those.”

AI displacement affects even graduate-level and post-college jobs.

According to technology guru Chris Messina, law and accounting are ready for AI. Messina warned some may be devastated. AI is changing medicine. Messina predicted “a huge shakeup” in law and accountancy.

“Many lawyers examine hundreds or thousands of pages of data and papers. Missing things is simple. An AI that can sift through and completely give the best contract for your result will definitely replace a lot of corporate attorneys.”

AI-based social manipulation

AI misuse includes social manipulation, according to 2018 research. In the 2022 election, Ferdinand Marcos, Jr. used a TikTok troll army to win over younger Filipino voters, proving this worry to be true.

TikTok’s AI system fills users’ feeds with similar material. This approach and the algorithm’s inability to filter hazardous and erroneous information have raised concerns about TikTok’s capacity to safeguard users.

Deepfakes have muddied politics and social media and news. The technology lets you swap figures in photos and videos. As a consequence, bad actors have another way to spread disinformation and war propaganda, making it practically hard to tell fact from fiction.

AI-based social surveillance

Ford worries about how AI will harm privacy and security in addition to its existential danger. China uses facial recognition in companies, schools, and other places. The Chinese government may collect enough data to trace a person’s actions, connections, and political opinions.

U.S. police use predictive policing algorithms to forecast crime locations. Arrest rates disproportionately affect Black neighborhoods, which affects these algorithms. Authorities subsequently over police these groups, raising issues about whether democracies can avoid turning AI into an authoritarian tool.

AI Biases

AI biases also harm. Humans produce AI, and people are prejudiced. Data and algorithmic bias may “amplify” each other.

“A.I. researchers are mostly male, who come from specific racial groups, who grew up in high socioeconomic regions, primarily individuals without disabilities,” Russakovsky added. “It’s hard to think globally since we’re a homogenous population.”

AI-Caused Socioeconomic Inequality

AI-powered hiring may jeopardize DEI projects if organizations ignore AI algorithms’ prejudices. Facial and voice analysis by AI still perpetuates racial prejudices in employment.

AI-driven job loss is another problem that shows AI’s class prejudices. Automation has reduced the wages of manual, repetitive blue-collar jobs by 70%. White-collar employees have been mostly unaffected and even paid more.

Claims that AI has overcome societal barriers or produced more employment are incomplete. Race, class, and other distinctions must be considered. Otherwise, determining how AI and automation help some and hurt others becomes harder.

AI weakening ethics and goodwill

Technologists, journalists, politicians, and religious leaders are warning about AI’s socio-economic risks. Pope Francis cautioned against AI’s propensity to “circulate tendentious thoughts and misleading facts” at a 2019 Vatican summit titled “The Common Good in the Digital Age” and warned of the dire repercussions of allowing this technology to evolve unchecked.

“If so-called technological progress were to get in the way of the common good,” he said, “this would be a sad return to a kind of barbarism where the strongest win.”

Others worry that we’ll keep pushing artificial intelligence if it makes money, no matter how many influential personalities warn us.

AI-Powered Weapons

“The essential dilemma for mankind now is whether to launch or avoid a global AI weapons race,” they said. If any major military force makes AI weapons, there will almost certainly be a global arms race. The goal of this technological path is clear: autonomous weapons will become the Kalashnikovs of the future.

Deadly autonomous weapon systems, which find and kill targets autonomously, have fulfilled this prediction. Some of the world’s most powerful countries have succumbed to fears and sparked a technological cold war as a result of the advancement of powerful and complex weaponry.

When autonomous weapons get into the wrong hands, they become even more dangerous to people. Hackers may infiltrate autonomous weapons and cause total destruction.

AI-Caused Financial Crises

AI algorithms don’t take into account settings, how markets are linked, how people trust and fear each other, or how people think or feel. These algorithms then conduct hundreds of deals in seconds to sell for modest gains. Selling thousands of transactions could scare other people into doing the same thing, which could cause the market to crash or be too volatile.

Whether deliberate or not, the 2010 flash crash and the Knight Capital flash crash show what may happen when trade-happy algorithms go nuts.

AI has value for finance. AI algorithms help investors make better market selections. Finance companies must understand their AI systems and how they make choices. Before using AI, companies should figure out if it makes investors feel more confident or less confident. This will help avoid investor worries and financial instability.

AI Risk Mitigation

AI still organizes health data and powers self-driving vehicles. Others say much more regulation is needed to maximize this promising technology.

AI Risk Mitigation

  1. Create global laws.
  2. Establish organizational 
  3. AI standards
  4. Humanize tech.

The U.S. and the European Union are making laws about AI clearer, which has been a top priority for many countries. This may outlaw certain AI technologies, but civilizations may still study them. Ford thinks AI is necessary for governments to develop and compete.

“You govern AI usage, but not a fundamental technology.” Ford remarked, “That’s foolish and dangerous.” “We determine where AI is allowed and where it isn’t. ц

The key is ethical AI use. Businesses may take several AI-integration initiatives. Companies may monitor algorithms, get high-quality data, and explain AI algorithm results. Leaders could even make AI a part of the way they do business by setting standards for AI technology.

Implementing ethical AI

“AI creators must seek the insights, experiences, and concerns of people across ethnicities, genders, cultures, and socio-economic groups, as well as those from other fields, such as economics, law, medicine, philosophy, history, sociology, communications, human-computer interaction, psychology, and Science and Technology Studies (STS).”

By balancing high-tech innovation with human-centered thinking, we can make sure that technology is used in a responsible way and that AI has a bright future. Leaders should acknowledge the risks of artificial intelligence so they can use it for good.

“We can speak about all these concerns, and they’re quite real,” Ford added. “But AI is also going to be our most significant tool for tackling our toughest challenges.”

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Artificial Intelligence

The Ethics of AI: What You Need to Know About Bias and Fairness

by Najam on
AI

AI is changing how businesses operate and interact with their customers. The technology enables automating simple, everyday tasks, provides data insights and helps people reach better-informed decisions. Yet, as AI becomes more common in IT, worries about how it could be used are growing.

More and more companies are starting to focus on how to stop AI from coming to conclusions that could be harmful. This deals with the ethical issues arising when computers process data and make decisions.

AI is a powerful technology with a vast array of advantageous qualities. Francesca Rossi, who is in charge of AI ethics for IBM around the world, thinks that we need to build a system of trust in both the people who make the technology and the technology itself to figure out how useful it could be. “Problems of bias, data handling, system capabilities,  explainability, openness on data policies, and design decisions should be handled responsibly and transparently,” the statement reads.

According to the CEO of the ethical consulting firm Ethical Intelligence and AI ethologist Olivia Gambelin, AI ethics should concentrate on comprehending how AI affects society, minimizing unintended effects, and encouraging beneficial global innovation. The author says that operationalizing AI ethics means turning abstract ideas into specific, measurable behaviors. The goal is to make sure that technology is based on human values at its core.

Risk or bias Areas for Artificial Intelligence

Kentaro Toyama, the W.K. Kellogg professor of community information at the University of Michigan School of Information, says that AI can be used in a lot of different ways, and many of them are already being used. Deep-fake photography gives visual “evidence” of flagrant falsehoods, killing decisions made by military drones using AI, and companies making money by buying and selling AI-based opinions about you. He adds that “algorithmic fairness” is another hot subject in AI ethics. 

Ethical Intelligence, Olivia Gambling

Scott Zoldi, chief analytics officer at FICO, an analytics company that specializes in credit scoring services, says that the excitement about AI is at odds with the harsh reality of machine learning models that were made and put into use quickly. He says that these models may achieve a certain business goal, but only at the cost of affecting different groups. Orporate users of machine learning models “become irresponsible and crass in their decision-making, frequently not even monitoring or questioning outcomes.”

Lama Nachman, who is in charge of Intel’s intelligent systems laboratories, says that AI systems often do well when they use the data they were trained on, but many do poorly when given new data from the real world. She also says, “This creates some safety problems, like an autonomous car misidentifying strange sights.” These [AI] systems must be overseen and monitored to prevent drift over time.

Discussion on AI Ethics

An organisation should develop and use AI technologies by following rules and guidelines called an “AI ethics policy.” Nachman says this strategy is “usually based on a risk analysis approach,” in which people who come up with ideas for, build, sell, and use these systems look at the risks often associated with AI technology. She says, “AI ethical principles generally include transparency, security, privacy, safety, inclusion, responsibility,  justice, and human supervision.”

A formalized AI ethical policy goes beyond being just desirable. Gambelin claims that even so, as more AI regulations are implemented and the market need for ethical technology increases, genuine survival demands are becoming more pressing. AI-driven businesses save time and money in the long run because they develop excellent and new solutions and use ethics as their primary tool for making decisions.

Perspective for AI Ethics

Businesses developing AI technology should consider ethical issues from the outset of their projects. According to Anand Rao, who oversees AI globally for the corporate consulting company PwC, “they must create the solutions from an ethical point of view.” With the launch of the product, ethics “cannot merely be a checkbox exercise,” he continues.

Just 35% of firms expect to enhance how AI systems and processes are managed as of 2021, and only roughly 20% of businesses now have an AI ethical framework. Rao anticipates better outcomes this year, though, since “responsible AI” was the CEOs’ top priority for AI in 2021.

IBM’s Rossi adds that to develop confidence in AI, business and IT executives must utilize a holistic, multidisciplinary, and multi-stakeholder approach.

The trust system should ensure people work together to find problems, talk about them, and solve them. She thinks this collaborative, multidisciplinary approach will give the best results and will most likely create a thorough and efficient environment for AI that can be trusted.

Gambelin says AI ethics is “a complicated field of passionate people and dedicated companies.”It notes that the field of AI ethics is at a crossroads. Our ability to use ethics as a tool will enable us to realize our goals and aspirations. This is a unique opportunity for humans to consider the benefits we hope to get from technology.

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Artificial Intelligence

What does it Mean for Creativity when AI can Make Art?

by Najam on
ai

The question of whether machines can be truly creative is a complex and controversial one, and opinions on this matter vary among experts and the general public. However, there are a few key points to consider.

On one hand, it is undeniable that AI algorithms are capable of producing outputs that can be considered creative, such as music, art, and literature. These algorithms use complex mathematical models to analyze patterns and generate new content based on the data they have been trained on. In some cases, the outputs are impressive and can even be mistaken for the work of human artists.

On the other hand, creativity is a complex human trait that involves a range of cognitive processes such as imagination, intuition, and emotional intelligence, which are not yet fully understood. Some argue that machines, no matter how advanced, cannot replicate the complexity and nuances of human creativity, as they lack consciousness and subjective experiences.

Moreover, there is an ongoing debate on the definition of creativity itself. Some argue that creativity is not just about producing novel or original content, but also about the intent behind it, the emotional impact it has on the audience, and the cultural and social context in which it is produced. Others believe that creativity is a universal trait that can be objectively measured and compared across different mediums and cultures.

In conclusion, while machines can certainly produce outputs that can be considered creative, the debate on whether they can truly be creative is ongoing and likely to continue as technology advances and our understanding of human creativity deepens.

The Capabilities of AI

The question of whether machines are truly creative is a complex and philosophical one that has generated a lot of discussion in recent years. While AI systems are certainly capable of producing outputs that can be considered creative, whether or not they are truly creative is still a matter of debate.

Creativity is a complex human trait that involves not just the ability to produce novel and original work but also the ability to understand and navigate social and cultural contexts. Human creativity is also often driven by emotions and motivations that are unique to individuals, which makes it difficult to replicate artificially.

While AI systems can certainly produce outputs that are impressive and indistinguishable from human-created work, they are ultimately limited by the data they have been trained on and the algorithms they are based on. They lack the subjective experiences and consciousness that are integral to human creativity.

Moreover, there is an ongoing debate over what constitutes creativity. Some argue that creativity is not just about producing novel or original content, but also about the intent behind it, the emotional impact it has on the audience, and the cultural and social context in which it is produced.

In conclusion, while machines can certainly produce outputs that can be considered creative, whether or not they are truly creative is still a matter of debate. As AI technology continues to advance, the boundaries between human and machine creativity may become increasingly blurred, and the definition of creativity itself may evolve to encompass new forms of output.

The Limitations of AI

While computers can generate new and original ideas and produce outputs that can be considered creative, their creativity is limited by the algorithms and data sets they have been trained on. Computers lack the ability to think creatively in the same way that humans do, as they do not have consciousness, emotions, and subjective experiences that are integral to human creativity.

Additionally, creativity often involves the ability to make connections between seemingly unrelated ideas, to imagine and empathize with different perspectives and experiences, and to express oneself in unique and meaningful ways. These are aspects of creativity that computers currently lack.

However, it is worth noting that as AI technology advances, researchers are exploring ways to make computers more creative and to enhance their capacity to generate original ideas. This may involve developing algorithms that can incorporate more randomness and unpredictability into the creative process or creating systems that can learn and adapt to new data and contexts. Nonetheless, the question of whether machines can truly be creative in the same way that humans are is still a matter of debate.

The Future of AI and Creativity

As AI technology continues to evolve and improve, machines may become more proficient at performing creative tasks. However, it is unlikely that machines will ever fully replace human creativity or the human creative process.

Human creativity is driven by a range of cognitive and emotional processes, including intuition, imagination, emotion, and experience, that are difficult to replicate artificially. The human creative process also involves subjective decision-making and an awareness of the cultural and social contexts in which the creative work is produced.

Therefore, AI’s greatest potential in the creative process may lie in its capacity to support and enhance human creativity. AI algorithms can be used to analyze and generate insights from large data sets, provide inspiration and generate ideas, and assist with the technical aspects of the creative process. By augmenting human creativity with AI, creators may be able to achieve greater efficiency and produce more innovative and impactful work.

Wrapping-up

The question of whether machines can truly be creative is a complex one that involves philosophical, scientific, and cultural considerations. While machines can produce outputs that are impressive and indistinguishable from human-created work, they lack the emotional depth, subjective experiences, and consciousness that are integral to human creativity.

As AI technology continues to develop, it is crucial to recognize and value the unique contributions of humans in the creative process. Machines can be used as tools to complement and enhance human creativity, rather than replace it. By combining the strengths of both humans and machines, creators may be able to achieve greater efficiency, generate new and innovative ideas, and produce work that is more impactful and meaningful.

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Artificial Intelligence

AI and Robotics: The Intersection of Intelligent Machines and Physical Automation

by Najam on
Physical Automation

Why do intelligent machines and physical automation have such a big intersection? Artificial intelligence and robotics are two fields that are rapidly evolving and have limitless possibilities for the human race’s future (AI). Robots that can do tasks with amazing speed and accuracy, from the simplest to the most complex and demanding in our everyday lives, are now possible thanks to advancements in robotics and artificial intelligence (AI). Is a new era in which humans will be replaced by more intelligent and powerful robots upon us when these two technologies converge?

Robots Among Men

Although AI and robotics have long been debated, during the last 20 years, the study and use of these technologies have increased. There is no longer a concern that these robots will displace humans from the workforce. Thanks to technologies like Alexa, Siri, Google Assistant, and others, we connect with robots and AI daily.

Knowledge Of Robotics And AI

Comprehending robots and AI might be difficult and complex, but it can also be a thrilling chance to investigate cutting-edge technology. The disciplines of robotics and artificial intelligence are developing quickly, with new developments occurring daily as these technologies offer a glimpse into the future of automation and human-computer interaction.

Although most people are used to using the terms interchangeably, robotics and artificial intelligence are two separate sciences. A branch of computer science and engineering called robotics involves creating and programming devices to carry out tasks autonomously. The term “artificial intelligence” (AI) refers to systems that can learn, solve problems, and make decisions independently without the assistance of previously programmed instructions.

Robotics is used in numerous fields today, including industry, healthcare, space exploration, and autonomous vehicles. Understanding how computers are taught intelligent behaviour utilising different machine learning approaches, such as networks, fuzzy logic, and deep learning, requires at least a fundamental understanding of AI technology.

Forward Toward the Future

There are still more ways that robotics and AI may be used, even if the end is now here since technology and innovation are at the core of everything we do. Only a handful of the regions are as follows:

Manufacturing: 

Manufacturing is a potential industry for robotics and AI since businesses are deploying robots in their factories and warehouses to increase productivity and save costs. Robots can also be utilised in industries like mining and construction, where using human labour could be dangerous. Meanwhile, artificial intelligence (AI) may play a crucial role in designing and manufacturing consumer goods by assisting engineers in developing new items that more effectively suit consumer wants.

Medicine: As technology develops, robots are utilised to provide care to patients in hospitals and long-term care institutions and to aid surgeons during delicate and intricate procedures. AI could also advance healthcare by analysing vast data and finding patterns that might help researchers and medical professionals better understand illnesses like cancer, liver, kidney, and heart problems.

Business: Using robotics in the workplace has several advantages, including improved productivity. Companies can finish jobs faster and with fewer mistakes when they deploy robots for activities that human workers now handle. Several companies are already using robotic package delivery. As this continues, some restaurants are deploying robots to do jobs like frying burgers and serving customers. This sort of innovation has the potential to boost productivity dramatically, allowing businesses to save money and stay competitive.

Why AI And Robotics Will Shape Our Future

Overall, the development of robotics and AI greatly enhance humanity’s future. Even though these technologies are still in their infancy, as long as researchers keep looking into their potential applications, we’ll see many more advancements in the future. The following five factors make robots and AI crucial to our future:

They may enhance our quality of life in sectors like education and even at home. Robotic humanoids are accelerating individualised learning. Cloud-connected robots at home can also do tasks like cooking and housework.

Several of the world’s most urgent issues, including climate change, energy instability, and healthcare issues, maybe resolved mainly because of them.

Many tiresome, repetitive daily jobs may be automated, freeing time and resources for more imaginative activities. There is a massive intersection of intelligent machines and physical automation.

They also give us new resources to help us comprehend and safeguard the environment around us, enabling us to build a more sustainable future for present and future generations.

They hold up the possibility of a more just and equal society where everyone can realise their full potential regardless of their upbringing or circumstances.

Conclusion

There’s no doubt that robots and AI could change the world, giving us more confidence and hope as we move into a future that is changing quickly. These new technologies are undoubtedly here to stay and will continue to play a large role in our lives, whether we embrace them or reject them.

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Artificial Intelligence

Explore the Possibilities of Quantum AI: Our Expert Solutions

by Najam on
Quantum AI

In recent years, the IT community has been very interested in quantum computing, and for a good reason. This state-of-the-art technology can fundamentally alter how we handle and store data, bringing about advancements in various industries, from artificial intelligence to encryption. So what is quantum computing precisely, and why is it so unique?

We’ll examine the potential applications of quantum computing in more detail in this blog article and explain what makes this technology such a game-changer.

Artificial Intelligence is constrained by the computing power of conventional computers while producing practical applications on them. Artificial Intelligence (AGI) may benefit from a computational boost from quantum computing, allowing it to handle more challenging issues.

Quantum computing: what is it?

A universal model known as quantum mechanics is built on ideas not found in everyday experience. A quantum model of the data is required for quantum computing to process data. For error correction and the proper operation of the quantum computer, hybrid quantum-classical models are also needed.

Quantum data For computerization, quantum data may be thought of as data packets housed in qubits. The qualities that make quantum data necessary, such as superposition and entanglement, also make it difficult to see and store. Moreover, because quantum data is noisy, machine learning must be used to evaluate and interpret this data appropriately.

Quantum-classical hybrid models Only when generating quantum data using quantum computers is it very probable to obtain nonsensical data. Because of this, a hybrid model develops when it is driven by quick data processing components like the CPU and GPU, which are typically employed in traditional computers.

Why is it crucial?

Although artificial intelligence (AI) has advanced quickly over the past ten years, it has yet to overcome technological constraints. Obstacles to obtaining AGI (Artificial General Intelligence) can be removed thanks to quantum computing’s unique properties. Machine learning models can be trained quickly with quantum computing, and the process may also be utilized to develop improved algorithms. Quantum computing’s optimized and reliable AI may speed up years of investigation and provide technological advancements. Some core issues facing modern AI include neuromorphic cognitive models, adaptive machine learning, and reasoning under uncertainty. 

How is quantum AI implemented?

An example of a set of tools that combines quantum modeling with machine learning methods is Google’s TensorFlow Quantum (TFQ), an open-source framework for quantum machine learning. TFQ aims to offer the tools required for modeling and controlling natural or created quantum systems.

Explore the Possibilities of Quantum AI

Quantum computing operates on the fundamental ideas of quantum physics to process data. This enables quantum computers to complete some tasks far more quickly than conventional computers and to resolve issues that would be impossible otherwise. One of the best things about quantum computing is that it can simultaneously handle a lot of data. This is especially helpful for jobs like data analysis and encryption.

Artificial intelligence is another field where quantum computing has a lot of potentials. Quantum computing has the potential to make AI systems more competent and effective because it can process huge amounts of data in real-time. Using quantum computing to make new, more accurate, and more effective AI algorithms could speed up the progress of AI research.

Quantum computing has many possible benefits, but it is still an increasing field. There are still a lot of obstacles to be cleared before it can fully realize its promise. This covers everything from building more powerful quantum computers to creating more complex algorithms and software that can benefit from the unique properties of quantum computing.

What critical junctures will quantum AI reach?

Quantum AI is still in its early stages, but advances in quantum computing are making it more useful. Quantum AI needs to reach a few milestones before it can move forward and become a more established technology. These achievements can be summed up as follows:

Many people use open-source modeling and training frameworks, making it easy to make AI apps that work better with quantum computing than traditional computing. The advancement of quantum AI will be made possible by these crucial developments.

Conclusion 

Quantum computing holds a lot of promise, and it’s a field of research that merits careful attention. Quantum computing is an area that has the potential to revolutionize the world in ways that we can only begin to imagine, whether you’re a researcher, a tech enthusiast, or just someone interested in the future of technology.

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