AI ML

AI and Machine Learning: Fictional to Functional

Experience the transformative power of AI and ML as they shape our world.

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Helius Work | AI and Machine Learning: Fictional to Functional - Image

Understanding AI and Machine Learning

Artificial intelligence is the expertise of computers to imitate human conception to carry out tasks in real-world set-ups.

Machine learning is about the algorithms and technologies that allow machines to understand the patterns, make informed decisions and enhance themselves via experience.

Artificial Intelligence

A program that can sense, reason, act, and adapt

Machine Learning

Algorithms whose performance improve as they are exposed to more data over time

Deep Learning

Subset of machine learning in which multilayers neural networks learn from vast amounts of data

Evolution of AI/ML

1950s – Birth of Artificial Intelligence

In times when computers were dependent on human brains, Alan Turing a British mathematician thought of computers to use coding to perform as per the program but can be customised to perform added functions. Alan developed the ” Turing test ” to check if AI can replicate human responses.

1960s – AI Roar

This year marked the launch of Artificial Intelligence at Dartmouth College by Marvin Minsky, Claude Shanon and John McCarthy. It was predicted that computers would perform all human tasks in the next twenty-five years.

1970s & 1980s – AI Winter

AI winter is the term that refers to a drop in research, interest and investment in this domain. This era started when AI researchers had to work with limitations like low processing speed and memory. Hence, they created machine translation systems which were utilized in the Cold War across the world.

Helius Work | AI and Machine Learning: Fictional to Functional - Ai Winter

1990s -Surge of Machine Learning

AI started using ML to help machines learn using data. Deep learning techniques evolved to help AI manage complex tasks which saw a considerable boost in robotics, speech recognition, computer vision and natural language processing.

2010s – AI Revival

It was the period of AI revival which saw deep learning advancements. AI systems attained immense success in virtual assistants, NLP and image recognition.

2020s (Present era): AI Integration

AI is integrated into different sectors and everyday lives including manufacturing, financial services, smart home devices etc.

Real-World Applications of AI/ML

AI has revolutionized multiple industries through its innovative solutions and changed the way businesses operate. Let us see some real-world applications of AI across different industries that reflect the strength and possibilities of AI in action.

Applications
of Al
Healthcare for assisting doctors
Education for automating grading system
Autonomous Vehicles for advanced features
Business for smoothening overall process
Travel Industry for predicting pricing pattern
Social Media for serving personalized experience

Healthcare

AI-backed diagnostic tools help physicians to offer precise diagnosis and relevant treatment plans. AI-powered robotic surgical equipment enables effective and minimal-risk treatments.

Finance

The finance sector can use AI algorithms to detect fraudulent activities, offer financial advice and optimize portfolios.

Transportation

AI has introduced autonomous vehicles which are transforming the transportation sector to a greater extent. Navigation programs based on AI technology offer real-time updates on traffic and optimize suggestions for different routes.

Marketing

AI-backed chatbots improve customer services by offering personalized support and prompt responses. AI helps analyse large volumes of customer data to offer targeted ads.

Travel

AI helps improve customer assistance, check prices for different locations and assess real-time information from different sources.

Limitations and Boundaries of AI and Machine Learning

Despite visible advancements in AI and ML in recent years, they too have certain boundaries and limitations like any other technology. It can have a major impact on real-world applications and hence needs careful consideration. So, let us explore the limitations and the boundaries of AI & ML.

Helius Work | AI and Machine Learning: Fictional to Functional - Ai-Ml

Decision Making

Artificial intelligence’s ability to make informed decisions with limited or incomplete data is one of the main limitations. AI algorithms can evaluate large volumes of data still the ability to comprehend the context & make decisions needs common sense. So, in uncertain situations, AI may not be able to make perfect decisions.

Bias Limitations

Due to the data, AI systems are fed and trained with, they remain unbiased only. For instance, if biased data is provided to an AI system, it will remain biased which can result in unfair results leading to discrimination mainly in finance, healthcare and hiring domains.

Absence of Creativity & Common Sense

AI can carry out multiple tasks like identifying images, processing language etc. Still, it lacks the creativity and common sense like humans. AI cannot think creatively or understand emotions like humour, sarcasm etc.

Machine Learning Boundaries

ML is a subcategory of AI which comes with its boundaries. ML algorithms cannot deal with the changes in data and try to match the data it is trained for very closely which results in poor performance.

Ethical Considerations

While using AI, you should know the ethical considerations attached to it. One of them is its capability for bias decision-making. So, the designers and developers creating AI systems should focus on the possibility of bias during the entire AI development cycle to design a system that can make unbiased decisions considering the objective criteria. Secondly, transparency should be considered by users who know how the system functions and what information it utilizes to make decisions. So, one needs to determine transparency, fairness, bias and accountability to ensure that AI is utilized correctly to address different challenges.

Impact of AI/ML on Work and Society in the Future

Helius Work | AI and Machine Learning: Fictional to Functional - Ai-Ml-future

AI is transforming the job market. It is bringing in new job profiles while automatic daily tasks. AI is expected to be introducing 20-50 million fresh jobs by 2030 in pharmacy, healthcare and several other industries.

1. Getting ready for the Future of Jobs

Artificial intelligence will impact the future of jobs in the coming years. Machine learning and automation will influence conventional job roles.

Parents should prepare their kids to adapt to the changing era. Focus on problem-solving, critical thinking ability with emotional intelligence and creativity to sustain in the AI world.

2. Automation and Job Losses

AI can automate and manage daily tasks effectively. It means for some jobs, the workforce may not be needed which means job layoffs. As per a Forbes survey, around 77% of people are worried about job losses due to AI in the coming years.  On the other hand, according to McKinsey, with the evolution of AI, job displacement of 400 million workers is estimated in coming years.

Job automation can affect jobs like legal services, office admin roles, sales, design etc.

3. Creation of Fresh Jobs

Well, despite the multiple concerns related to job losses, it is predicted that job automation can lead to the creation of several fresh jobs. Let us check out the statistics.
  • Year 2022- 39% of businesses hired software engineers & 35% hired certified data engineers for various AI-related profiles
  • AI is estimated to introduce nearly 97 million fresh jobs. For example, AI teachers, data scientists, data scientists, human-machine teaming managers etc.

4. Economic Boost

We can see growth in our economy with AI integration. As per the studies, AI can boost productivity and GDP growth. Hence, AI’s impact may not be even and result in job losses but also introduces new career prospects at the same time in other industries.

The Future of
AI
Technologies

Artificial intelligence market to grow to $90 billion by 2025

75%

of c-level executives believe that artificial intelligence will enable their organizations to grow and achieve competitive advantage

There will be more Al assistants in the world than people.
It is predicted that by 2024, there will be 8.4 billion Al-based digital voice assistants in the world, exceeding the total global population

By 2025, Al could eliminate 85 million jobs but create 97 million new ones, resulting in a net gain of 12 million jobs

80%

of business will switch to intelligent automation by 2025

Conclusion

Technology is changing at a faster pace and so are the job roles, AI and automation are transforming business operations and we can see their impact on multiple industries. While some job roles may be at risk due to automation, others are progressing with the use of Artificial intelligence.

AI will continue to grow and hence we need to think proactively about the right way to use it for the benefit of society and the workers. We need to adapt to the digital shift to sustain. We cannot identify the possible job losses but can build strategies that eradicate the risk of layoffs and train workers to get into new roles. Let us recognize the challenges of AI and focus on responsible AI development to ensure AI helps us make the most of technological advancement.

Author:

Kavya Dave

Kavya Dave, a fresh Computer Science graduate and AI enthusiast, loves building products that solve real-life problems. With a knack for product strategy, implementation, and data analysis, she excels in creating impactful solutions. A true people person, Kavya is dedicated to making technology accessible and effective.

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We assure you that your investment in healthcare IT solutions will lead to tangible success, whether in improving patient care, streamlining operations, or advancing technological innovation within the industry