#scope of artificial intelligence and machine learning

[cybtekk]

Discover the limitless potential of your career as a software developer in the dynamic realms of Artificial Intelligence (AI) and Machine Learning (ML). "Unlock Your Future" opens doors to unparalleled opportunities, guiding you through the transformative landscape of AI and ML.

[kids-worldfun]

Scope for Growth after B Tech in Artificial Intelligence and Machine Learning

In recent years, artificial intelligence and machine learning had an impact on nearly every industry. As Andrew Ng (Computer Scientist and Global Leader in AI) observed, “It is difficult to think of a major industry that AI has not affected and will not transform. The industries experiencing a major impact of AI technologies include education, healthcare, retail, e-commerce services, agriculture,…

[notanannoyingfangirl]

Key Trends Shaping the Future of Corporate Compliance

Corporate compliance functions are entering a new era of rapid transformation, driven by technological advances, regulatory shifts and stakeholder pressures surrounding sustainability. By understanding critical developments in compliance operating models, risk management approaches and oversight frameworks, leaders can proactively position their organizations for long-term success.

Digitization to Enable “Compliance by Design”

Automation through robotic process automation (RPA), artificial intelligence and advanced analytics is empowering next-generation compliance. Machine learning facilitates real-time audits, gathering intelligence across transactions, communications and ecosystem signals to identify regulatory exposure. Self-updating compliance manuals tuned to latest ordinance shifts are on the horizon. The end vision is embedding compliance through system design across operations.

Focus Expanding Beyond Narrow Regulations

With intensifying scrutiny by investors, employees and society on ethical conduct, compliance roles are ballooning beyond narrowly meeting legal obligations alone to championing holistic integrity. Leading organizations are tying codes of conduct to societal value frameworks addressing diversity, sustainability and equitable impacts surrounding products and services. Data transparency, anti-corruption and human rights commitments are rising in priority.

Centralized Governance with Localized Operations

Global companies are moving towards centralized compliance governance under chief ethics/compliance officers and committees to align policies while localizing procedures. Geographic and divisional compliance heads are being empowered to tailor training programs using cultural nuances and localized languages to make integrity standards intuitively resonate across borders rather than appear disconnected edicts from headquarters.

Ultimately corporate compliance is maturing into a value creation function contributing towards trust and transparency with stakeholders rather than merely a check-the-box necessity. As guardians of integrity underpinning quality, fairness and reliability commitments made across supply chains and communities, compliance is becoming an ethical backbone driving capitalism’s next chapter.

[catboybiologist]

Many billionaires in tech bros warn about the dangerous of AI. It's pretty obviously not because of any legitimate concern that AI will take over. But why do they keep saying stuff like this then? Why do we keep on having this still fear of some kind of singularity style event that leads to machine takeover?

The possibility of a self-sufficient AI taking over in our lifetimes is... Basically nothing, if I'm being honest. I'm not an expert by any means, I've used ai powered tools in my biology research, and I'm somewhat familiar with both the limits and possibility of what current models have to offer.

I'm starting to think that the reason why billionaires in particular try to prop this fear up is because it distracts from the actual danger of ai: the fact that billionaires and tech mega corporations have access to data, processing power, and proprietary algorithms to manipulate information on mass and control the flow of human behavior. To an extent, AI models are a black box. But the companies making them still have control over what inputs they receive for training and analysis, what kind of outputs they generate, and what they have access to. They're still code. Just some of the logic is built on statistics from large datasets instead of being manually coded.

The more billionaires make AI fear seem like a science fiction concept related to conciousness, the more they can absolve themselves in the eyes of public from this. The sheer scale of the large model statistics they're using, as well as the scope of surveillance that led to this point, are plain to see, and I think that the companies responsible are trying to play a big distraction game.

Hell, we can see this in the very use of the term artificial intelligence. Obviously, what we call artificial intelligence is nothing like science fiction style AI. Terms like large statistics, large models, and hell, even just machine learning are far less hyperbolic about what these models are actually doing.

I don't know if your average Middle class tech bro is actively perpetuating this same thing consciously, but I think the reason why it's such an attractive idea for them is because it subtly inflates their ego. By treating AI as a mystical act of the creation, as trending towards sapience or consciousness, if modern AI is just the infant form of something grand, they get to feel more important about their role in the course of society. Admitting the actual use and the actual power of current artificial intelligence means admitting to themselves that they have been a tool of mega corporations and billionaires, and that they are not actually a major player in human evolution. None of us are, but it's tech bro arrogance that insists they must be.

Do most tech bros think this way? Not really. Most are just complict neolibs that don't think too hard about the consequences of their actions. But for the subset that do actually think this way, this arrogance is pretty core to their thinking.

Obviously this isn't really something I can prove, this is just my suspicion from interacting with a fair number of techbros and people outside of CS alike.

[mediaevalmusereads]

Gods and Robots: Myths, Machines, and Ancient Dreams of Technology. By Adrienne Mayor. Princeton University Press, 2018.

Rating: 4/5 stars

Genre: classics, mythology

Series: N/A

Summary: The fascinating untold story of how the ancients imagined robots and other forms of artificial life—and even invented real automated machines The first robot to walk the earth was a bronze giant called Talos. This wondrous machine was created not by MIT Robotics Lab, but by Hephaestus, the Greek god of invention. More than 2,500 years ago, long before medieval automata, and centuries before technology made self-moving devices possible, Greek mythology was exploring ideas about creating artificial life—and grappling with still-unresolved ethical concerns about biotechne, “life through craft.” In this compelling, richly illustrated book, Adrienne Mayor tells the fascinating story of how ancient Greek, Roman, Indian, and Chinese myths envisioned artificial life, automata, self-moving devices, and human enhancements—and how these visions relate to and reflect the ancient invention of real animated machines.As early as Homer, Greeks were imagining robotic servants, animated statues, and even ancient versions of Artificial Intelligence, while in Indian legend, Buddha’s precious relics were defended by robot warriors copied from Greco-Roman designs for real automata. Mythic automata appear in tales about Jason and the Argonauts, Medea, Daedalus, Prometheus, and Pandora, and many of these machines are described as being built with the same materials and methods that human artisans used to make tools and statues. And, indeed, many sophisticated animated devices were actually built in antiquity, reaching a climax with the creation of a host of automata in the ancient city of learning, Alexandria, the original Silicon Valley.A groundbreaking account of the earliest expressions of the timeless impulse to create artificial life, Gods and Robots reveals how some of today’s most advanced innovations in robotics and AI were foreshadowed in ancient myth—and how science has always been driven by imagination. This is mythology for the age of AI.

***Full review below.***

CONTENT WARNINGS: descriptions of myths that include violence and bestiality, mention of slavery

I first heard of this book when Adrienne Mayor was a guest on the Mindscape podcast. I found her ideas and arguments to be interesting, so I figured her book would expand on the concepts she explored on the podcast.

Overall, I think this book is an accessible intro for readers interested in classical studies and the history of science. Mayor writes clearly and without a lot of specialized terminology, so even if you're new to classics, you won't find this book difficult. I think the chapter about Talos was the most convincing and the most well-done, bringing together textual analysis and art history in a way I found intellectually pleasing.

As a scholar, however, I think this book could have gone a bit further, especially with its analysis of myths and texts. Mayor summarizes most of the myths she discusses, which is all well and good for situating the reader in the texts. But what I really wanted was more specific evidence and close reading: were there any interesting language choices used to describe this automaton? Did the Greeks have a certain vocabulary for artificial beings? As it stands, it felt like Mayor's textual analysis relied on general ideas, and while fine as a starting point, I really think it could have been pushed.

I also think there's some room to apply critical frameworks such as posthumanism and transhumanism theory. Applying such theories would enhance the meanings Mayor is trying to get at, but in all fairness, this may he beyond the scope of the book. Mayor seems to be relaying a history of ideas rather than trying to get at their interpretation, so maybe her book will function well as a springboard for other scholars and students to do this work.

Lastly, I do think this book could have been framed a little better to help me as a reader see some of the through-lines. There were moments when I wasn't sure how each of Mayor's examples fit in with the overall theme of "robots" or "artificial life," so maybe a better framing device would be the theme of biotechne rather than the sci fi approach that the book currently uses. Similarly, some further delineation between what constitutes "technology" versus magic (and even just "art") would have been helpful for seeing how each individual chapter builds upon the previous.

TL;DR: Gods and Robots is a good overview of the history of artifical life and technology in the ancient Greek world. This book is perhaps most useful as a springboard for further analysis, and historians, art historians, and literary scholars will find plenty to build on.

[pandeypankaj]

What's the difference between Machine Learning and AI?

Machine Learning and Artificial Intelligence (AI) are often used interchangeably, but they represent distinct concepts within the broader field of data science. Machine Learning refers to algorithms that enable systems to learn from data and make predictions or decisions based on that learning. It's a subset of AI, focusing on statistical techniques and models that allow computers to perform specific tasks without explicit programming.

On the other hand, AI encompasses a broader scope, aiming to simulate human intelligence in machines. It includes Machine Learning as well as other disciplines like natural language processing, computer vision, and robotics, all working towards creating intelligent systems capable of reasoning, problem-solving, and understanding context.

Understanding this distinction is crucial for anyone interested in leveraging data-driven technologies effectively. Whether you're exploring career opportunities, enhancing business strategies, or simply curious about the future of technology, diving deeper into these concepts can provide invaluable insights.

In conclusion, while Machine Learning focuses on algorithms that learn from data to make decisions, Artificial Intelligence encompasses a broader range of technologies aiming to replicate human intelligence. Understanding these distinctions is key to navigating the evolving landscape of data science and technology. For those eager to deepen their knowledge and stay ahead in this dynamic field, exploring further resources and insights on can provide valuable perspectives and opportunities for growth 

[shadowmaat]

OTW concerns

I know the OTW is vital for preserving fannish things. Pretty much my life's work is hosted on AO3 and I have spent many years happily convinced that AO3 would look out for the best interests of fans and donating money to that cause when I could.

Unfortunately, doubts have begun to creep in. Last year's election debacle was it's own whole thing, but the most recent issue has to do with AI and the OTW's stance on it.

I've sent them a couple of letters now expressing my concerns and been told that it's a "complex issue" and that the Board is indeed giving it a lot of thought. They were frustrating but fair responses since I understand that it IS a complex issue and coming to a consensus can be difficult.

Time is still passing, however, with no official word on what the Organization is planning to do. No official word... except from their Legal Chair, Betsy Rosenblatt.

In the latest OTW Signal of May 2023, they shared an excerpt (and link to) an interview Betsy gave regarding the use of AI in relation to fanfic. This was done, apparently, for Fair Use/Fair Dealing Week, and Ms. Rosenblatt's opinions seem to focus more on future potential than current reality, which is troubling.

Ms. Rosenblatt believes that content scraping is good for teaching "AI" programs about modern language usage and views. The use of "AI" to generate fics seems to fall under the scope of "fair use" as far as she's concerned. Which would seem to indicate that, from Legal's standpoint, there's nothing wrong with continuing to allow bots to scrape content from AO3 and regurgitate it into new content.

It could also mean that people posting AI-generated content onto AO3 under the guise of them being legitimate works will also be allowed to continue.

I think that true artificial intelligence is a fascinating concept. I also understand that these programs need to learn somehow, but stealing stories (and art) without permission or credit is fucking reprehensible and should not be tolerated at any level. The fact that the Legal Chair for one of the most vital fan archives on the internet seems to be in favor of this is... alarming. Especially since, as far as I know, no other Board members have spoken up in opposition.

I also really dislike that Ms. Rosenblatt seems entirely concerned about what's "good" for machine learning and not at all about what's good for the human fans who are the entire reason the OTW exists.

AO3 is the backbone of fandom on the internet, but this is a bad direction for it to go, if that is indeed the way it's planning to go.

[unilifeabroadcareersolution]

Popular Courses Currently in Demand for International Students

@unilifeabroadcareersolutions

Popular courses currently in demand for international students After finding the perfect course, any international student must make another crucial decision when choosing which course to study abroad in. Global industries are currently changing fast, and it can create career opportunities for international students depending upon the fields they choose and the scope for Permanent Residency (PR). So here is a list of some of the top in-demand courses for international students looking to study abroad in 2024 and beyond. 1. Data Science and Artificial Intelligence

With the emergence of big data and AI-driven technologies, Data Science and AI have emerged as two of the most in-demand courses worldwide.

Why Choose It?

High-paying job opportunities. Demand in industries like IT, healthcare, finance, and retail. Courses available in countries like USA, Canada, Germany, and UK. Career Prospects: Data Scientist, AI Engineer, Machine Learning Expert, Data Analyst. 2. Engineering and Technology

Engineering is at the top preference of the international students due to a wide range of area and scope. Some of the most common specializations offered are Mechanical, Civil, Electrical, and Software Engineering.

 Why to choose? All over the world, engineers are required for every industry, such as construction, automobile, and technological. Many colleges provide industrial training along with co-op programs. Top Destinations: Germany, Canada, Australia, and USA. Career Opportunities: Software Engineer, Project Manager, Structural Engineer, Robotics Specialized.

3. Business Administration and Management (MBA) A Master of Business Administration (MBA) is ideal for students who want to work in a leadership position or become an entrepreneur. There is a growing trend towards specialized MBAs in Finance, Marketing, Human Resources, and Operations.  Why Choose It?  International recognition and high-paying jobs.  Networking opportunities and exposure to real-world business.  Popular Places: USA, UK, Canada, and Australia.  Career Paths: Business Consultant, Marketing Manager, Operations Director, Financial Analyst. 4. Healthcare and Nursing The health sector is on a roll due to the growing need for qualified professionals. Nursing, Public Health, Physiotherapy, and Pharmacy courses are highly rewarded. Why Study It?  High employability and PR opportunities in countries like Canada, Australia, and UK.  Good chance to make a good difference in people's life. Career Options: Registered Nurse, Public Health Specialist, Pharmacist, Physiotherapist. 5. Information Technology and Cyber security The increased dependency on technology has given a huge demand for IT and Cyber security professionals. Courses like Cloud Computing, Cyber security, and Software Development are in high demand. • Why Choose It? Tremendous job opportunities in tech-driven economies like the USA, Canada, and Germany. Increased demand for cyber security experts to combat digital threats. Career Options: Cyber security Analyst, IT Consultant, Software Developer, Cloud Architect.

6. Hospitality and Tourism Management the tourism industry is on a boom after the pandemic, and so are the demands for professionals in Hospitality and Tourism Management. Why Choose It? Global opportunities for working in luxury hotels, airlines, and tourism companies. Strong industry links and placement during courses. • Popular Locations: Switzerland, Australia, France. • Career Opportunities: Hotel Manager, Tourism Consultant, Event Planner, Airline Executive. 7. Environmental Science and Sustainability As there is a growing interest in sustainability across the globe, courses in Environmental Science, Renewable Energy, and Climate Change are on demand • Why study it? Large-scale efforts at creating the sustainable world present a massive employment scope. • Job opportunities with governments, NGOs, and private sectors Career Prospects: Environmental Consultant, Sustainability Officer, Renewable Energy Specialist. 8. Finance and Accounting Courses on finances and accounting are always in high demand all over the world. FinTech, Financial Technology, and all the related courses are in trends these days. Why Choose It? • High demand for finance people in the world. PR opportunities in Canada and Australia • Career Options: Accountant, Financial Analyst, Investment Banker, FinTech Specialist. 9. Media and Communications The dawn of digital media, content creation, and advertising has made Media and Communications one of the most exciting and rewarding fields. Why Choose It? Growing job demand in digital marketing, PR, and content strategy. Opportunity for creativity and innovation. Career Options: Digital Marketer, Media Specialist, Content Creator, Public Relations Officer. 10. Logistics and Supply Chain Management Supply Chain Management has become a necessary professional skill for international businesses considering the booming of globalization and e-commerce

Why Choose It? Logistics, transportation and e-commerce sectors are demanded. Strong employment opportunities in Canada, Germany and USA. Career Options: Supply chain analyst, logistics manager and procurement specialist. Conclusion The right course according to global trends and industry demand is the key to a successful future. Whether it's technology, healthcare, or business, the top courses in demand are here, offering excellent career opportunities and pathways for PR. Explore programs that align with your interests and goals, and take the first step toward achieving your dream career abroad.

[elsa16744]

Big Data and AI: The Perfect Partnership for Future Innovations 

Innovation allows organizations to excel at differentiation, boosting competitive advantages. Amid the growth of industry-disrupting technologies, big data analytics and artificial intelligence (AI) professionals want to support brands seeking bold design, delivery, and functionality ideas. This post discusses the importance of big data and AI, explaining why they matter to future innovations and business development. 

Understanding Big Data and AI 

Big data is a vast data volume, and you will find mixed data structures because of continuous data collection involving multimedia data objects. A data object or asset can be a document, an audio track, a video clip, a photo, or identical objects with special file formats. Since big data services focus on sorting and exploring data objects’ attributes at an unprecedented scale, integrating AI tools is essential. 

Artificial intelligence helps computers simulate human-like thinking and idea synthesis capabilities. Most AI ecosystems leverage advanced statistical methods and machine learning models. Their developers train the AI tools to develop and document high-quality insights by processing unstructured and semi-structured data objects. 

As a result, the scope of big data broadens if you add AI integrations that can determine data context. Businesses can generate new ideas instead of recombining recorded data or automatically filter data via AI-assisted quality assurances. 

Why Are Big Data and AI Perfect for Future Innovations? 

1| They Accelerate Scientific Studies  

Material sciences, green technology projects, and rare disorder research projects have provided humans with exceptional lifestyle improvements. However, as markets mature, commoditization becomes inevitable. 

At the same time, new, untested ideas can fail, attracting regulators’ dismay, disrespecting consumers’ beliefs, or hurting the environment. Additionally, bold ideas must not alienate consumers due to inherent complexity. Therefore, private sector stakeholders must employ scientific methods to identify feasible, sustainable, and consumer-friendly product ideas for brand differentiation.  

AI-powered platforms and business analytics solutions help global corporations immediately acquire, filter, and document data assets for independent research projects. For instance, a pharmaceutical firm can use them during clinical drug formulations and trials, while a car manufacturer might discover efficient production tactics using AI and big data. 

2| Brands Can Objectively Evaluate Forward-Thinking Business Ideas 

Some business ideas that a few people thought were laughable or unrealistic a few decades ago have forced many brands and professionals to abandon conventional strategies. Consider how streaming platforms’ founders affected theatrical film releases. They have reduced the importance of box office revenues while increasing independent artists’ discoverability. 

Likewise, exploring real estate investment opportunities on a tiny mobile or ordering clothes online were bizarre practices, according to many non-believers. They also predicted socializing through virtual reality (VR) avatars inside a computer-generated three-dimensional space would attract only the tech-savvy young adults. 

Today, customers and investors who underestimated those innovations prefer religiously studying how disrupting startups perform. Brands care less about losing money than missing an opportunity to be a first mover for a niche consumer base. Similarly, rejecting an idea without testing it at least a few times has become a taboo. 

Nobody can be 100% sure which innovation will gain global momentum, but AI and big data might provide relevant hints. These technologies are best for conducting unlimited scenario analyses and testing ideas likely to satisfy tomorrow’s customer expectations. 

3| AI-Assisted Insight Explorations Gamifies Idea Synthesis 

Combining a few ideas is easy but finding meaningful and profitable ideas by sorting the best ones is daunting. Innovative individuals must embrace AI recommendations to reduce time spent on brainstorming, product repurposing, and multidisciplinary collaborations. Furthermore, they can challenge themselves to find ideas better than an AI tool. 

Gamification of brainstorming will facilitate a healthy pursuit of novel product features, marketing strategies, and customer journey personalization. Additionally, incentivizing employees to leverage AI and big data to experiment with designing methods provides unique insights for future innovations. 

4| You Can Optimize Supply Chain Components with Big Data and AI Programs 

AI can capture extensive data on supply chains and offer suggestions on alternative supplier relations. Therefore, businesses will revise supply and delivery planning to overcome the flaws in current practices. 

For instance, Gartner awarded Beijing’s JD.com the Technology Innovation Award in 2024 because they combined statistical forecasting. The awardee has developed an explainable artificial intelligence to enhance its supply chain. Other finalists in this award category were Google, Cisco, MTN Group, and Allina Health. 

5| Academia Can Embrace Adaptive Learning and Psychological Well-Being 

Communication barriers and trying to force all learners to follow the standard course material based on a fixed schedule have undermined educational institutions’ goals worldwide. Understandably, expecting teachers to customize courses and multimedia assets for each student is impractical and humanly infeasible. 

As a result, investors, policymakers, parents, and student bodies seek outcome-oriented educational innovations powered by AI and big data for a learner-friendly, inclusive future. For instance, some edtech providers use AI computer-aided learning and teaching ecosystems leveraging videoconferencing, curriculum personalization, and psycho-cognitive support. 

Adaptive learning applications build student profiles and segments like marketers’ consumer categorizations. Their AI integrations can determine the ideal pace for teaching, whether a student exhibits learning disabilities, and whether a college or school has adequate resources. 

Challenges in Promoting Innovations Based on Big Data and AI Use Cases 

Encouraging stakeholders to acknowledge the need for big data and AI might be challenging. After all, uninformed stakeholders are likely to distrust tech-enabled lifestyle changes. Therefore, increasing AI awareness and educating everyone on data ethics are essential. 

In some regions, the IT or network infrastructure necessary for big data is unavailable or prone to stability flaws. This issue requires more investments and talented data specialists to leverage AI tools or conduct predictive analyses. 

Today’s legal frameworks lack provisions for regulating AI, big data, and scenario analytics. So, brands are unsure whether expanding data scope will get public administrators’ approvals. Lawmakers must find a balanced approach to enable AI-powered big data innovations without neglecting consumer rights or “privacy by design” principles. 

Conclusion 

The future of enterprise, institutional, and policy innovations lies in responsible technology implementations. Despite the obstacles, AI enthusiasts are optimistic that more stakeholders will admire the potential of new, disruptive technologies. 

Remember, gamifying how your team finds new ideas or predicting the actual potential of a business model necessitates AI’s predictive insights. At the same time, big data will offer broader perspectives on global supply chains and how to optimize a company’s policies. 

Lastly, academic improvements and scientific research are integral to developing sustainable products, accomplishing educational objectives, and responding to global crises. As a result, the informed stakeholders agree that AI and big data are perfect for shaping future innovations.  

[cybtekk]

Software developers with AI & ML skills have a wide range of career opportunities which gives a promising growth too. With the evolution of technology, the demand for professionals in this field will remain strong.

[onlinemedicalconsultation14]

The Evolution and Benefits of Online Medical Consultation

The digital age has revolutionized many aspects of our lives, including how we access healthcare. Online medical consultations, also known as telemedicine, have become increasingly popular, providing patients with access to healthcare professionals from the comfort of their own homes. This shift has been driven by the convenience, accessibility, and efficiency that online consultations offer, particularly in a world where time is precious and health concerns can arise unexpectedly.

Accessibility and Convenience

One of the most significant benefits of Online Medical Consultation is their accessibility. Traditionally, accessing healthcare could involve long waiting times for appointments, travel to a healthcare facility, and time spent in waiting rooms. Online consultations eliminate these barriers by allowing patients to connect with healthcare providers from anywhere, at any time. This is particularly beneficial for those living in remote or rural areas, where access to healthcare can be limited.

Additionally, the convenience of online consultations is unmatched. With the ability to schedule appointments at a time that suits the patient, there is no need to take time off work or arrange for childcare. This flexibility is especially valuable for those with busy schedules or mobility issues, ensuring that healthcare is accessible to everyone, regardless of their circumstances.

Efficiency and Cost-Effectiveness

Online medical consultations are not only convenient but also efficient. Many health concerns, such as common colds, allergies, skin conditions, and mental health issues, can be addressed effectively through virtual consultations. This allows healthcare providers to diagnose and treat patients quickly, without the need for an in-person visit. In many cases, prescriptions can be issued, and follow-up care can be managed remotely, reducing the need for multiple appointments.

Moreover, online consultations can be more cost-effective than traditional healthcare. Patients save on travel costs and time, while healthcare providers can manage their time more effectively, seeing more patients and reducing overhead costs associated with maintaining a physical clinic. This cost-effectiveness can make healthcare more affordable and accessible, particularly for those without comprehensive insurance coverage.

Challenges and Future Prospects

Despite the many benefits, online medical consultations do come with challenges. One of the primary concerns is the lack of physical examination, which can be crucial for diagnosing certain conditions. However, advances in technology, such as wearable health devices and remote monitoring tools, are helping to bridge this gap, allowing for more accurate and comprehensive virtual care.

Furthermore, concerns around data security and patient privacy must be addressed as telemedicine continues to grow. Healthcare providers must ensure that the platforms they use are secure and comply with regulations to protect patient information.

Looking ahead, the future of online medical consultations is promising. As technology continues to advance, the scope of what can be achieved through virtual healthcare will expand. The integration of artificial intelligence, machine learning, and advanced diagnostic tools will enhance the capabilities of online consultations, making them an increasingly viable option for a wider range of health concerns. As society becomes more comfortable with digital solutions, online medical consultations are likely to become a standard part of healthcare, providing patients with accessible, efficient, and cost-effective care.

[vedangkadia]

How AI is changing Digital Marketing What is Digital Marketing?

Digital marketing is defined as a process of selling goods and services via digital media which includes Social media, Emails, search engines, and websites. Such a method is useful in that it expands the scope of business reach and provides interaction with the target audience impossible in marketing. Some of the digital marketing techniques are content marketing, search engine optimization, influencer marketing, and web advertising. Through these channels, businesses can define the intended audience to cascade the campaigns, monitor the impact of the campaigns, and make real-time adjustments. This means that the marketing activities being carried out are more productive and result-oriented hence creating more business out of the whole marketing exercise.

What is AI?

AI stands for artificial intelligence and is considerably described as the ability of machines to imitate one or all aspects of human intelligence. AI is also described in broader terms which associates it with machine learning and natural language processing, robotics, and other disciplines. These technologies allow an AI system to have the ability to identify speech, decide, and translate between languages. For digital marketing, AI facilitates the analysis of large data sets, automation and, providing the right messages to the right customers. This in turn improves the existing marketing plan and possibilities to narrow down the focus and interact with clients.

How AI is Changing Digital Marketing:

AI is now disrupting the digital marketing field due to the methods it offers that help refine the data gathering and handling approaches, customer targeting, and campaign customization processes. AI algorithms are capable of processing huge amounts of information and making analysis concerning consumer behavior faster as compared to human beings; marketers can use the results of such analysis to develop finer and better campaigns. Besides, others like email marketing, commercial posting, etc., can also be automated by AI leaving the marketers with only the key tasks to deal with and think of. Consequently, commercial organizations reach better Returns on Investment, and customers tend to develop friendly relations with businesses.

Myth or Truth - Is AI Transforming the Digital Marketing Industry?

The matter of fact is still open, whether AI is just a fancy word utilized in discourse connected with digital marketing or a driving force that evolves this field. Nevertheless, numerous examples and cases show that the role of AI in modern industry is exceptionally important. It has been noted that companies applying AI have seen a relative enhancement in customer interaction, leads, and sales. Leverage in customer care; services such as chatbots and other analytical tools that incorporate the use of Artificial intelligence are becoming core assets to the marketing strategies of companies. Although there are barriers that can be encountered in the adoption of AI, the advantages of the technology are considerably faster in comparison to the liabilities, which makes AI a significant resource for the modern marketer.

Why Use AI?

Thus, AI provides many benefits in the context of digital marketing. Some of the tasks it can effectively accomplish include data entry, marketing through emails, and social media among others since it cuts across many people and may contain many errors. AI also enables the marketers to know the customers better hence, enhancing the chances of the marketers to develop unique content and campaigns. This leads to an increase in the level of customer satisfaction and thereby customers’ loyalty. In the same way, AI may also facilitate the utilization of advertising budget on the most convertible leads, and hence, bigger conversion ratios, paving the way to enhanced ad spend potentiality. Altogether, the application of AI is beneficial to companies as it enhances their marketing goals’ accomplishment.

What are the Pros and Cons of AI in Marketing?

Pros:

1) Improved A/B Testing:

AI can perform A/B tests rather quickly and this would not be possible if it was done entirely by the human resource. It enables the marketer to know which content is more effective and which strategy yields the best results. AI can also narrow down the results and provide real-time analysis of the tests that a person undertakes. Improved A/B testing leads to a better understanding of what resonates with the audience and higher conversion rates.

2) Targeted Lead Generation and Client Segmentation:

AI is used to draw insights to identify leads and categorize clients according to their actions and choices. It also makes it possible for marketing communication to be focused on the prospects that are most likely to produce good results. AI can determine which of the leads are most likely to turn into buyers and therefore give them priority. This is a very important approach in marketing because it makes businesses address the right audience hence boosting their chances of success and return on investment.

3) Content Creation Written by AI:

AI can write blog posts, social media updates, product descriptions, or any kind of textual content. These tools employ artificial intelligence and specifically natural language processing to produce quality content that will appeal to the target audience. This assists marketers in having a proper and continuous flow of content and hence managing the workload. Despite the occasional need for human intervention in training the AI, it can help in the generation of content quite swiftly and provide a continuous stream of new content.

4) Timely Messaging:

AI ensures that marketing messages are delivered at the correct time to capture the attention of the audience it is intended for. It identifies the frequency of operation and timing to approach the users. This in turn increases the chances of the messages being opened and answered by the recipients. Mailing should be done at the appropriate time so that the customers can show interest in the products and make purchases. And since users are mostly likely to be active at those times, businesses have a better shot at achieving higher marketing outcomes.

5) Self-Learning:

AI systems can remember previous conversations and even experience learning regarding interactions with customers. This makes them more potent as time progresses. For example, AI can learn from the kind of feedback it has been receiving or the level of users’ engagement. This self-learning capacity means that AI tools will not only stay current in an ever-evolving digital environment but will also adapt their operation for optimum efficiency. AI systems will continue to improve over the next five years and will become more effective at understanding the customers’ needs and fulfilling them.

Cons:

1) High implementation costs:

Consideration of AI in marketing often implies considerable costs such as acquisitions of hardware and software and training of employees. As is explained, it could be challenging to establish the initial expenditures for the technology, especially for small businesses; thus, the competition with large organizations may be tough. The financial cost of AI technology can be a significant obstacle to entry, particularly for startups and small businesses.

2) Requires technical expertise:

This presents a challenge for some businesses because marketers themselves require or should possess the skills to effectively use these tools. This frequently requires recruiting specialists or providing additional training to in-house workers, which can be both time-consuming and expensive. Furthermore, AI technology is constantly developing and changing, so it is crucial to educate oneself constantly and adapt to new information and programs.

3) Potential loss of jobs:

In the future, as AI continues to absorb more activities, there is potential for jobs with repetitive work to become obsolete. This can even lead to job insecurity and make it necessary for the company to look for methods of repurposing the involved employees. The change might be dramatic for both the employee and employer since it causes drastic alternation of the employees’ positions.

4) Data privacy concerns:

AI applied in marketing means that large amounts of data are being gathered and analyzed, thus there may be privacy concerns. Since data is managed within businesses, care should be taken to respect the laws on data protection and also retain the trust of consumers. Not doing so may incur legal consequences and affect the brand image negatively in the process.

5) Dependence on technology:

One disadvantage of relying on AI functionalities is that these systems are prone to technical glitches and breakdowns. Marketing can also be inhibited when AI systems fail or are not maintained appropriately, which will further affect the performance of the business. Also, reliance on these technologies may limit human supervision and analytical capabilities in the decision-making processes.

Will AI Replace Digital Marketers?

AI is not a threat to digital marketers but rather will change the nature of the work that digital marketers do. Marketers will also require more strategy, imagination, and certainly, a clear understanding of AI technologies. AI will manage and analyze data and automate tasks so that marketers will be in a better position to make wise decisions. This shift will also entail the marketers to change course learn new skills and adapt to the new technologies. Thus, although AI can be very useful in marketing initiatives, creativity, and strategy will never be fully delegatable to AI systems. With digital marketers and AI in place, there will be even better and enhanced marketing techniques in the future.

What’s the Future of AI in Digital Marketing?

Based on the various scenarios that have been presented AI has a bright future in digital marketing and its future will not only be shaped by the existing technologies but also the future advancements that will provide a better way of doing the existing. Leveraging the power of AI will open up opportunities to greatly enhance the quality of the insights generated about customers and provide unprecedented predictive modeling based on real-time information.

Consumers will benefit also because marketers will be able to direct-read their audiences and, therefore, provide them with highly personalized content. Moreover, the use of AI in these marketing strategies will display an extended effectiveness with increased risk. The application of AI is bound to become more integrated into digital marketing as it becomes more advanced and this can be seen as a key factor that cannot be overlooked by business establishments that want to compete effectively in today’s diverse market.

What are the Different Types of AI?

1) Machine Learning:

When it comes to artificial intelligence, machine learning is a component that enables systems to learn with experience and demonstrate scaling. It involves the use of various models that are incorporated into a computer to assess a given element, discover a given pattern, or else project a given trend. In digital marketing, machine learning has particular uses in customer segmenting, predictive analysis, and recommendation systems. This is especially advantageous in marketing because machine learning enables the system to constantly learn from data and adapt the model to be more accurate with subsequent cycles.

2) AI Assistants & Chatbots:

AI helps through its customer support tool: AI assistants and/or chatbots respond to clients within the shortest time possible and the responses can handle all the questions that may be presented at one time. They employ natural language processing to parse customer inquiries and allow representatives to respond. These tools assist businesses in penetrating the market and responding to customer inquiries and complaints faster. For instance, customers can engage with chatbots to help in making suggestions, knowing the status of their orders, and the handling of complaints. It also improves the quality of the overall customer service experience and enables human agents to tackle specific and detailed jobs.

3) Voice Search:

Voice search is a type of search engine that is spoken to by the users to get the required results. Computing gadgets, including smart home appliances such as speak-to-me devices such as Siri, Alexa, Google Assistant, etc are also frequently initiated. Therefore, marketers should balance how their content will be processed by the voice search to increase its visibility. They include the application of natural language, response to frequently asked questions, and sharing of pertinent information. Leveraging it shall be an added advantage for businesses as consumers continue to shift towards voice search engine results.

4) Marketing Automation & Personalization:

AI makes marketing functions an automated process where it can control tasks like email to customers, social media posts, and advertising. It also does that rather in line with the personal characteristics of the users of the software application. This makes sure that the marketing message that is to be relayed whether through the printed media or any other medium is appealing to the interests and the relevance of the consumers. For instance, the subject lines of promotional emails sent can be personalized, product suggestions based on the user’s past actions, or even the advertisement location can be tweaked. This level of personalization also decreases the possibility of one making the wrong decisions since it will always result in conversion and improved customer satisfaction.

The Future of Digital Marketing is Here:

AI which was long associated with a future technology is already part of digital marketing today. AI can also be used to improve the results of marketing plans and strategies by firms. AI tools or solutions enhance data productivity, specialized content development, and self-service customers. The above tools help marketers to provide high user engagement and create more meaningful interactions with the audiences. Thus, AI remains an ever-evolving feature of the digital marketing field which, as the technology develops, will remain an inseparable part of modern marketing.

Conclusion:

AI as a tool is the future of digital marketing benefiting it in various ways like better user experience, better segmentation, and customer analytics.  It is therefore clear that even with the implementation of AI the job of digital marketers will be shifted and not eliminated. This means that marketers are to concentrate on strategy and creativity in marketing while on the other hand, AI covers the analytical workload and automation of routine tasks. This paper aims to address how there is a need for firms to adopt the technology of AI to remain relevant and provide effective marketing communication. Digital marketing with the help of AI is not just another hype that can be a part of the trend, it is a massive change that has come to stay. Any business that will accept this great change will be in a vantage position to thrive in the increasingly digital economy.

Let's wrap up with this thought: Let me know your thoughts on this: What do you think about AI in digital marketing? Intrigued by what it can do for your strategy, to change the game and take it to the next level?

[techpaathshala]

Artificial Intelligence (AI):

Definition: AI refers to the broader concept of machines being able to carry out tasks in a way that we would consider “smart.” It encompasses various technologies that allow machines to mimic human intelligence.

Scope: Includes machine learning, natural language processing, robotics, and more.

Machine Learning (ML):

Definition: ML is a subset of AI that focuses on the ability of machines to learn from data, identify patterns, and make decisions with minimal human intervention.

Scope: Primarily involves algorithms and statistical models that enable computers to perform specific tasks without using explicit instructions.

[mariacallous]

Over the summer, a political action committee (PAC) supporting Florida governor and presidential hopeful Ron DeSantis uploaded a video of former president Donald Trump on YouTube in which he appeared to attack Iowa governor Kim Reynolds. It wasn’t exactly real—though the text was taken from one of Trump’s tweets, the voice used in the ad was AI-generated. The video was subsequently removed, but it has spurred questions about the role generative AI will play in the 2024 elections in the US and around the world.

While platforms and politicians are focusing on deepfakes—AI-generated content that might depict a real person saying something they didn’t or an entirely fake person—experts told WIRED there's a lot more at stake. Long before generative AI became widely available, people were making “cheapfakes” or “shallowfakes.” It can be as simple as mislabeling images, videos, or audio clips to imply they’re from a different time or location, or editing a piece of media to make it look like something happened that didn’t. This content can still have a profound impact if they’re allowed to circulate on social platforms. As more than 50 countries prepare for national elections in 2024, mis- and disinformation are still powerful tools for shaping public perception and political narratives.

Meta and YouTube have both responded in recent months with new policies around the use of generative AI in political ads like the one in support of DeSantis. Last month, Meta announced that it would require political advertisers to disclose whether an ad uses generative AI, joining Google, which owns YouTube, in responding to concerns that newly available tools could be used to mislead voters. In a note on its blog post about how the company is approaching the upcoming 2024 elections, Meta says that it will require advertisers “to disclose when they use AI or other digital techniques to create or alter a political or social issue ad in certain cases.”

“The scope is only political ads, which is a tiny part of the political ecology where people are increasingly using AI-generated media,” says Sam Gregory, program director at the nonprofit Witness, which helps people use technology to promote human rights. “It's not clear that it covers the broad range of shallowfakes or cheapfake approaches that are already being deployed both in political ads, but also, of course, in much broader ways that people use in political context.”

And not all misleading political content ends up in advertisements. For instance, in 2020, a video went viral that made it appear like Representative Nancy Pelosi was slurring her speech. The video itself wasn’t fake, but it had been slowed down to make Pelosi appear drunk. Though Twitter, TikTok, and YouTube removed the video, it remained live on Facebook, with a label noting it was “partly false.” The video itself wasn’t an ad, though it was clearly targeting a political figure.

Earlier this year, Meta’s Oversight Board took on a case reviewing doctored video of President Joe Biden, which had not been generated or edited using AI, and which the company left up on the platform. The board will use the case to further review the company’s “manipulated media policy,” which stipulates that videos where “a subject … said words that they did not say” and which are “the product of artificial intelligence or machine learning” will be removed. Content like the Pelosi and Biden videos don't clearly violate this policy. Manipulated audio, particularly problematic in many non-English contexts, is nearly completely left out.

“Political ads are deliberately designed to shape your emotions and influence you. So, the culture of political ads is often to do things that stretch the dimensions of how someone said something, cut a quote that's placed out of context,” says Gregory. “That is essentially, in some ways, like a cheap fake or shallow fake.”

Meta did not respond to a request for comment about how it will be policing manipulated content that falls outside the scope of political advertisements, or how it plans to proactively detect AI usage in political ads.

But companies are only now beginning to address how to handle AI-generated content from regular users. YouTube recently introduced a more robust policy requiring labels on user-generated videos that utilize generative AI. Google spokesperson Michael Aciman told WIRED that in addition to adding “a label to the description panel of a video indicating that some of the content was altered or synthetic,” the company will include a more “more prominent label” for “content about sensitive topics, such as elections.” Aciman also noted that “cheapfakes” and other manipulated media may still be removed if it violates the platform’s other policies around, say, misinformation or hate speech.

“We use a combination of automated systems and human reviewers to enforce our policies at scale,” Aciman told WIRED. “This includes a dedicated team of a thousand people working around the clock and across the globe that monitor our advertising network and help enforce our policies.”

But social platforms have already failed to moderate content effectively in many of the countries that will host national elections next year, points out Hany Farid, a professor at the UC Berkeley School of Information. “I would like for them to explain how they're going to find this content,” he says. “It's one thing to say we have a policy against this, but how are you going to enforce it? Because there is no evidence for the past 20 years that these massive platforms have the ability to do this, let alone in the US, but outside the US.”

Both Meta and YouTube require political advertisers to register with the company, including additional information such as who is purchasing the ad and where they’re based. But these are largely self-reported, meaning some ads can slip through the company’s cracks. In September, WIRED reported that the group PragerU Kids, an extension of the right-wing group PragerU, had been running ads that clearly fell within Meta’s definition of “political or social issues”—the exact kinds of ads for which the company requires additional transparency. But PragerU Kids had not registered as a political advertiser (Meta removed the ads following WIRED’s reporting).

Meta did not respond to a request for comment about what systems it has in place to ensure advertisers properly categorize their ads.

But Farid worries that the overemphasis on AI might distract from the larger issues around disinformation, misinformation, and the erosion of public trust in the information ecosystem, particularly as platforms scale back their teams focused on election integrity.

“If you think deceptive political ads are bad, well, then why do you care how they’re made?” asks Farid. “It’s not that it’s an AI-generated deceptive political ad, it’s that it’s a deceptive political ad period, full stop.”