2024 is set to be a groundbreaking year for AI and machine learning, with exciting advancements and pivotal changes on the horizon. From multimodal AI to evolving regulations, we dive deep into the trends that will shape the future of technology.
In this video, we cover:
Multimodal AI - How AI is processing multiple input types like text, images, and sound.
Agentic AI - The rise of proactive AI systems that act independently.
Open Source AI - Making advanced AI accessible to all through open-source models.
Retrieval-Augmented Generation (RAG) - Combining text generation with information retrieval for better accuracy.
Customized Enterprise Generative AI Models - Tailoring AI models to specific business needs.
Demand for AI and Machine Learning Talent - The growing need for skilled professionals in AI and ML.
Shadow AI - Addressing the risks of unauthorized AI tool usage in organizations.
Generative AI Reality Check - Real-world challenges in scaling AI applications.
Increased Focus on AI Ethics and Security - Ensuring transparency and fairness in AI systems.
Evolving AI Regulation - Understanding new regulatory frameworks like the EU's AI Act.
Stay ahead of the curve and learn how these trends can impact your business and daily life. Whether you're a tech enthusiast, a business leader, or just curious about the future, this video is packed with valuable insights!
OUTLINE:
00:00:00
Top 10 AI and Machine Learning Trends in 2024
00:00:30
AI That Sees, Hears, and Understands
00:01:24
The Rise of AI That Acts
00:02:16
Democratizing the Power of AI
00:03:05
Making AI Smarter with External Knowledge
00:03:58
Tailoring AI to Specific Needs
00:05:03
The Skills You Need to Thrive in the AI Age
00:05:52
The Unseen Risks of Unsanctioned AI Use
00:06:56
From Hype to Practical Implementation
00:07:42
Building Trust in the Age of AI
00:08:38
Navigating the Legal Landscape of AI
00:09:37
Staying Ahead of the Curve
#MachineLearning #ArtificialIntelligence #TechTrends #FutureTech #AITechnology #Innovation #AI2024 #MLTrends #TechUpdates #GenerativeAI #MultimodalAI #AIEthics #TechNews #AIRegulation #OpenSourceAI #TechFuture #AIRevolution #SmartTech #NextGenAI
In this video, we cover:
Multimodal AI - How AI is processing multiple input types like text, images, and sound.
Agentic AI - The rise of proactive AI systems that act independently.
Open Source AI - Making advanced AI accessible to all through open-source models.
Retrieval-Augmented Generation (RAG) - Combining text generation with information retrieval for better accuracy.
Customized Enterprise Generative AI Models - Tailoring AI models to specific business needs.
Demand for AI and Machine Learning Talent - The growing need for skilled professionals in AI and ML.
Shadow AI - Addressing the risks of unauthorized AI tool usage in organizations.
Generative AI Reality Check - Real-world challenges in scaling AI applications.
Increased Focus on AI Ethics and Security - Ensuring transparency and fairness in AI systems.
Evolving AI Regulation - Understanding new regulatory frameworks like the EU's AI Act.
Stay ahead of the curve and learn how these trends can impact your business and daily life. Whether you're a tech enthusiast, a business leader, or just curious about the future, this video is packed with valuable insights!
OUTLINE:
00:00:00
Top 10 AI and Machine Learning Trends in 2024
00:00:30
AI That Sees, Hears, and Understands
00:01:24
The Rise of AI That Acts
00:02:16
Democratizing the Power of AI
00:03:05
Making AI Smarter with External Knowledge
00:03:58
Tailoring AI to Specific Needs
00:05:03
The Skills You Need to Thrive in the AI Age
00:05:52
The Unseen Risks of Unsanctioned AI Use
00:06:56
From Hype to Practical Implementation
00:07:42
Building Trust in the Age of AI
00:08:38
Navigating the Legal Landscape of AI
00:09:37
Staying Ahead of the Curve
#MachineLearning #ArtificialIntelligence #TechTrends #FutureTech #AITechnology #Innovation #AI2024 #MLTrends #TechUpdates #GenerativeAI #MultimodalAI #AIEthics #TechNews #AIRegulation #OpenSourceAI #TechFuture #AIRevolution #SmartTech #NextGenAI
Category
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LearningTranscript
00:00Welcome back to the channel everyone. Today, we're diving deep into the world of AI. We're
00:09talking about the big trends, the game changers that are going to reshape the tech landscape
00:13in 2024. Remember when chat GPT dropped? It was like the whole world woke up to what AI
00:20could really do. Now, things are about to get really interesting. Let's break down
00:25the top 10 AI and machine learning trends you absolutely need to know about in 2024.
00:31All right, first up, let's talk about multimodal AI. Multimodal AI is all about breaking down
00:39barriers between different types of data. We humans experience the world through multiple
00:44senses, sight, sound, touch. Multimodal AI aims to do the same. It can process images,
00:51audio, text, even sensor data, all at the same time. Imagine showing an AI a picture
00:56of ingredients on a counter. It could recognize them, understand their properties, and suggest
01:01a recipe. OpenAI's GPT-4 is already dipping its toes into the multimodal pool. It can
01:07analyze images and respond to prompts that combine both text and visuals. We're talking
01:12about AI that can help doctors diagnose diseases, power robots to navigate complex environments,
01:18and even help you design a website. This technology has the potential to revolutionize
01:22entire industries. Now, if multimodal AI is about perception,
01:30agentic AI is all about action. We're talking about AI that doesn't just wait for instructions
01:35but can actually set its own goals and figure out how to achieve them. Imagine an AI assistant
01:40that's not just responding to your commands but is actively anticipating your needs. Need
01:45to book a flight? Your agentic AI has already scanned for the best deals and times. Got
01:50a deadline coming up. It's already prioritizing your tasks and clearing your schedule. But
01:55agentic AI goes way beyond personal assistance. We're talking about AI that can manage entire
02:00systems, optimize complex processes, and even make critical decisions in real time. This
02:06is the kind of AI that could help us solve some of the world's biggest challenges. The
02:10future of agentic AI is still being written, and it's up to us to make sure it's a future
02:15we can all be excited about. So far, we've talked about AI that can see
02:21and understand like us, AI that can act autonomously. Now, let's talk about who gets to build and
02:27use this technology. That's where open source AI comes in. Open source AI is changing the
02:33game by making powerful AI models available to the public. Take Metasllama 2, for example.
02:39It's a powerful language model that's completely open source. This means researchers, developers,
02:44and small businesses can now access cutting edge AI capabilities without having to build
02:48everything from scratch. Open source AI fosters innovation and promotes transparency and collaboration.
02:55Of course, there are challenges like the risk of misuse and sustainability. But overall,
03:01open source AI represents a fundamental shift in how we think about AI development.
03:10Retrieval Augmented Generation, or RAG, making AI smarter with external knowledge. Traditional
03:15language models rely solely on the data they've been trained on, which can lead to issues
03:19like hallucinations. RAG addresses this by giving AI models access to external knowledge
03:24bases. Instead of just relying on its internal memory, RAG allows AI to consult a vast library
03:31of information in real time. This means the AI can pull in relevant facts, figures, and
03:37context to provide more accurate and comprehensive responses. RAG improves the accuracy and reliability
03:44of AI-generated content. It allows AI models to stay up to date with the latest information,
03:50and it can help reduce the size and complexity of AI models. RAG offers a powerful approach
03:55to achieving more trustworthy and informative AI applications.
04:03Customized Enterprise Generative AI Models, tailoring AI to specific needs. Instead of
04:10relying on one-size-fits-all solutions, companies are realizing that they can get better results
04:15by building or fine-tuning AI models specifically for their industry, their data, and their
04:21workflows. By training AI models on their own data, businesses can create AI solutions
04:27that are more accurate, more efficient, and more aligned with their specific goals. This
04:32approach allows businesses to leverage their own data to create a competitive advantage.
04:38Customized AI models can be more cost-effective and offer greater control over data privacy
04:43and security. We're already seeing this trend play out across industries. Financial institutions
04:49are building custom AI models to detect fraud and assess risk. Healthcare providers are
04:54developing AI-powered diagnostic tools tailored to specific patient populations. The era of
04:59one-size-fits-all AI is giving way to a more nuanced approach.
05:06Chapter Six. The Demand for AI and Machine Learning Talent, the Skills You Need to Thrive
05:11in the AI Age. The demand for AI and machine learning talent is exploding. Businesses need
05:18data scientists, machine learning engineers, and AI ethicists. One of the most in-demand
05:24skills is AI programming, with Python being the go-to language. Data analysis is another
05:29crucial skill. MLOps, or machine learning operations, is about managing the entire lifecycle
05:35of AI models. It's not just about technical skills. Diverse perspectives are crucial for
05:40fair and unbiased AI development. Whether you're a seasoned developer or just curious
05:44about AI, there's never been a better time to dive in and learn new skills. The AI revolution
05:49is here, and it's creating opportunities for those who are ready to seize them.
05:56Chapter Seven. Shadow AI, the Unseen Risks of Unsanctioned AI Use. Shadow AI happens
06:01when employees use AI tools without the IT department's knowledge or approval. This can
06:07create security issues, as unsanctioned AI tools might not have the same level of security
06:11protocols. It can also lead to compliance issues, as different industries have different
06:17regulations around data privacy and usage, and it can create inconsistencies in workflows
06:23and make it difficult to track results. Companies need to educate their employees about the
06:28potential risks of using unsanctioned AI tools, and establish clear guidelines for AI adoption.
06:34It's about finding a balance between fostering innovation and ensuring responsible AI use.
06:40Companies need to create an environment where employees feel comfortable experimenting with
06:43new technologies, but also understand the importance of security, compliance, and ethical
06:49considerations. The rise of shadow AI highlights the need for proactive AI governance within
06:55organizations.
06:57Okay, let's be real for a second. There's a lot of hype around AI, but as companies
07:03move from the experimental phase to actually integrating AI into their core operations,
07:09they're encountering real-world challenges. One of the biggest hurdles is data quality.
07:13AI models are only as good as the data they're trained on. Another challenge is system integration.
07:18AI needs to seamlessly integrate with existing systems and workflows. Building, deploying,
07:24and managing AI systems requires specialized skills and knowledge. It's crucial for companies
07:29to set realistic expectations about what AI can and cannot do. By focusing on practical
07:36data quality and clear business value, companies can harness the true power of AI to drive
07:41meaningful results.
07:45As AI becomes more powerful and pervasive, it's more important than ever to address the
07:50ethical and security implications of this technology. One of the biggest concerns is
07:54AI bias. AI models are trained on data, and if that data reflects existing societal biases,
08:01the AI model will perpetuate those biases. Another concern is the lack of transparency
08:06in AI decision-making. Many AI models are often described as black boxes because it
08:11can be difficult to understand how they arrive at their decisions. And then there's the issue
08:15of AI security. Addressing these challenges requires developing ethical guidelines and
08:20principles for AI development and deployment. Promoting diversity and inclusion in the AI
08:26workforce is essential for identifying and mitigating potential biases. Building trust
08:31in AI is about ensuring that AI is developed and used in a way that is ethical, responsible,
08:37and aligned with human values.
08:40All right, we've talked about the technical trends and ethical considerations, but we
08:46can't forget about the legal landscape. As AI becomes more integrated into our lives,
08:51governments around the world are grappling with how to regulate this rapidly evolving
08:55technology. One of the most significant developments in AI regulation is the European Union's
09:00AI Act. It's a landmark piece of legislation that aims to create a comprehensive framework
09:06for AI governance. The AI Act categorizes AI systems into different risk levels, with
09:12higher risk systems subject to stricter requirements. While the AI Act is specific to the EU, it's
09:18likely to influence AI regulations globally. For businesses, navigating this evolving regulatory
09:24landscape can be challenging. It requires staying informed about new regulations and
09:29adapting practices to ensure compliance. AI regulation is essential for building trust
09:34in AI and ensuring its responsible development and deployment.
09:41So there you have it, the top 10 AI and machine learning trends that are shaping the future.
09:47From AI that can see and understand like us, to the ethical considerations and evolving
09:52regulations, it's clear that AI is no longer a futuristic concept. It's here, and it's
09:57transforming the world around us. Whether you're a tech enthusiast, a business leader,
10:02or just someone who's curious about the future, staying informed about these trends is crucial.
10:07AI is going to impact every aspect of our lives from the way we work and communicate
10:13to the way we solve global challenges. If you found this video helpful, don't forget
10:17to give it a thumbs up and subscribe to the channel for more insights into the world of
10:22AI and machine learning. And be sure to let me know in the comments which trend you found
10:26most interesting or surprising.