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Gen AI’s Next Leap: Predicting the Future of Artificial Intelligence in 2024 and Beyond

In recent years, artificial intelligence has transformed from a futuristic concept into a dynamic and influential force across various industries. A striking statistic from Deloitte’s Managing Director, Manoj Suvarna, highlights this evolution: Generative AI (GenAI) has become more mainstream than ever before, reshaping traditional business workflows and introducing novel content creation methods​​. This article delves into the current landscape and Gen AI’s next leap, exploring how it’s poised to continue revolutionizing the way we live and work.

Rise of Gen AI

2023 marked a significant breakthrough for generative AI. It evolved from a novel technology to a mainstream tool, deeply integrated into businesses and creative processes. ChatGPT, a prominent example, showcased the potential of GenAI in automating complex tasks such as content creation, software development, and image generation. This mainstream adoption is changing the game, compelling organizations to adopt private large language models (LLMs) not just as an enhancement but as a necessity to stay competitive​​.

The practical applications of GenAI are vast. In content creation, for instance, it’s no longer about automating mundane tasks; it’s about crafting unique, engaging content that resonates with audiences on a deeper level. Similarly, in software development, GenAI is not just streamlining processes but also enabling the creation of more sophisticated, user-centric software. Tech companies have started training their workforce to be able to use AI tools and increase productivity. 

The underlying implication is profound: organizations leveraging GenAI are not just optimizing their operations; they’re redefining their industry landscapes.

Challenges and Innovations in AI Hardware

However, this rapid growth in AI capabilities is not without its challenges, particularly in hardware. A major concern as we step into 2024 is the global shortage of GPU processors, critical for running AI applications. This shortage is a result of increased demand from big companies seeking to internalize AI capabilities. Notably, NVIDIA, a major GPU manufacturer, is struggling to meet this skyrocketing demand​​.

This challenge is spurring innovation in AI hardware. Experts at Stanford, including professors like Kunle Olukotun and Chris Re, are exploring low-power alternatives to current GPUs. These efforts are crucial in democratizing AI technology, making it accessible beyond the big players. The development of new hardware solutions is not just about meeting current demands; it’s about future-proofing AI technology, ensuring that it remains sustainable and accessible as it becomes increasingly woven into the fabric of our society​​.

AI-Powered Agents and Multimedia

The landscape of AI is set to evolve remarkably in 2024, with a significant shift towards more interactive and multi-functional AI agents. The previous year laid the groundwork, mainly focusing on chat-based AI interactions. But the upcoming year promises to leap beyond this, enabling AI agents to perform real-world tasks like making reservations, planning trips, and seamlessly connecting to various services. This evolution marks a transition from AI as a conversational tool to a practical assistant capable of executing tasks autonomously​​.

In multimedia, AI’s potential is expanding rapidly. Until now, the focus has primarily been on language and image models. However, the integration of video processing is on the horizon. This advancement is particularly intriguing because video data provides a new dimension of unfiltered, continuous information that AI models haven’t processed before. It could lead to a more profound understanding of real-world events and behaviors, significantly enhancing AI’s predictive and analytical capabilities​​.

Importance of AI Governance and Ethics

As AI becomes increasingly integrated into various aspects of society, the need for robust governance and ethical frameworks grows more urgent. In 2024, we can expect more concrete actions and policies in this area. Governments and organizations worldwide are recognizing the risks associated with bias, inequality, and discrimination in AI algorithms. Consequently, there’s a move towards implementing guardrails and governance policies to mitigate these risks. The U.S. White House Executive Order and emerging regulations in Europe are indicative of this global shift towards responsible AI usage​​.

In addition, the calls for transparency and responsible development in AI are expected to grow stronger. This focus on ethical AI development reflects a broader societal demand for technology that not only advances capabilities but also respects and protects human rights and values. This shift is not just about avoiding harm; it’s about leveraging AI in a way that positively contributes to society, fostering trust and acceptance among the general public​​.

AI in the Workplace

The impact of AI on the workforce is a crucial trend for 2024. AI adoption in the workplace is enhancing processes, boosting productivity, and reshaping income structures. It’s a double-edged sword, however, as it also brings the potential for significant job displacement. To counterbalance this, there will be a heightened emphasis on the reskilling and upskilling of employees. The future workplace will likely see the emergence of new roles such as AI ethicists and prompt engineers, illustrating the transformative effect of AI on job landscapes​​.

A Goldman Sachs report suggests that AI could trigger a productivity boom, potentially increasing the total annual value of global goods and services by 7%. This signifies a profound shift in the nature of work, where certain skills will become obsolete while others, like analytical judgment and emotional intelligence, will become more valuable. The integration of AI in the workplace is not just about automation; it’s about creating a more dynamic, skill-focused, and efficient workforce​​.

AI in Various Industries

In 2024, we’ll witness AI’s growing influence across a wide array of industries, reshaping them in innovative ways. The healthcare sector, for example, will see AI-driven enhancements in patient communication, disease detection, and support for healthcare professionals. In education, AI is expected to revolutionize learning experiences through innovative content and personalized tutoring systems. Manufacturing will benefit from AI in rapid prototyping, digital twinning, and optimizing production processes​​.

Each industry will experience AI’s transformative power differently, but the common thread is the move toward efficiency, precision, and personalization. For instance, in e-commerce, AI is set to offer more tailored shopping experiences, while in agriculture, it could lead to more efficient and sustainable farming practices. There are many case studies on such solutions built by tech companies like Mantra Labs. This widespread application signifies AI’s versatility and its potential to solve industry-specific challenges​​.

Data Protection and Privacy in the Age of AI

As AI technologies become more pervasive, the importance of data protection and privacy is increasingly highlighted. AI TRiSM (Trust, Risk, and Security Management) is gaining prominence as a framework to help organizations comply with data privacy regulations. By 2026, it’s expected that companies using AI TRiSM to manage their AI systems will significantly improve decision-making by eliminating inaccurate or fake data​​.

This trend underscores the necessity of balancing AI’s potential with the need to protect individual privacy. As AI systems often contain sensitive personal data, ensuring their security and compliance with data privacy laws is crucial for maintaining public trust and ethical standards in AI deployment.

Personalization Through AI

Personalization is a key trend in AI for 2024, especially in app development. Gartner predicts that by 2026, a third of all new apps will use AI to create personalized and adaptive user interfaces, a significant increase from today’s numbers. This shift is driven by AI’s ability to analyze user data and preferences, offering tailored content and experiences. Companies excelling in AI-powered personalization are expected to generate significantly more revenue from these activities compared to their peers​​.

Emergence of Quantum AI

Quantum AI, the fusion of quantum computing and AI, is an emerging field poised to open new possibilities in various domains. It could revolutionize financial modeling, and drug discovery, and even contribute to the development of Artificial General Intelligence (AGI). The global Quantum AI market is anticipated to reach a significant value by 2030, growing at a robust rate. This synergy between quantum computing and AI has the potential to dramatically enhance computational power and efficiency, paving the way for groundbreaking advancements​​.

Legislative Landscape for AI

The advancement and integration of AI into daily life necessitate the development of comprehensive legislation to govern its use. Laws and regulations will be crucial in ensuring AI is used responsibly and ethically. As AI can be utilized for both positive and negative purposes, having a legal framework in place is essential for guiding its development and application in a manner that aligns with societal values and norms​​.

Wrapping Up

Looking ahead to 2024 and beyond, AI is set to continue its transformative journey, impacting every facet of our lives. From enhancing workplace productivity to reshaping entire industries and necessitating robust governance frameworks, AI’s potential is boundless. As we embrace these advancements, it’s crucial to balance innovation with ethical considerations, ensuring AI’s development benefits society as a whole. The future of AI is not just about technological prowess; it’s about how we harness this power to create a more efficient, equitable, and sustainable world.

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Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

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Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform. 

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Source: getport.io

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization:  Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

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