Name: Infrastructure for AI: Flexibility, Cost and Adaptability
Start: 2021-02-09T17:00:00Z
End: 2021-02-09T17:01:03.000Z
Location: BrightTALK
Rating: 4.5

Each month, the AI: the Future of Business series explores the latest trends, technologies and best practices in the world of Enterprise AI and sheds light on Artificial Intelligence for the modern business.


Artificial Intelligence is transforming the landscape of Human Resources, offering innovative solutions for talent acquisition and management. This webinar explores how AI is reshaping HR practices, enhancing efficiency, and driving better outcomes.

Join Ramesh Dontha and guests as they discuss: 

 -  How AI is reshaping recruitments, onboarding and employee retention 
-  The value of AI-powered hiring platforms 
-  How HR departments are adopting AI to streamline talent management and improve the employee experience
-  Best practices for leveraging AI responsibly in HR, including ensuring fairness and mitigating bias

This session will provide valuable insights and actionable strategies for HR professionals looking to harness the power of AI to revolutionize their talent acquisition and management processes.

AI in Human Resources: Revolutionizing Talent Acquisition and Management

As AI continues to transform industries, it’s also reshaping the workforce. With the potential to enhance productivity and collaboration, and even create new roles, AI is sure to be the driving force for a lot of change to the workforce we know today. 

Join Ramesh Dontha and guests in this webinar, as they discuss: 

-  How AI is impacting job roles
-  The skills required for the future, and how businesses can prepare their employees for an AI-driven workplace
-  The balance between human labor and automation
-  Strategies for upskilling the workforce

AI and the Future of Work: Redefining Jobs and Skills

With AI systems entrusted with handling unprecedented volumes of personal data, the intersection of privacy and security has never been more critical. As businesses navigate the complex landscape of AI-driven data processing, prioritizing privacy considerations alongside innovation is now a top priority for any business handling personal data. 

Join us in this webinar as Ramesh Dontha and guests discuss: 

-  The balance between innovation and privacy
-  How businesses can responsibly handle customer data while still leveraging AI for personalization and insights
-  The latest regulations and compliance requirements

AI and Personal Data: Balancing Innovation and Privacy

The rapid evolution of AI-driven customer service tools, such as chatbots and virtual assistants, is revolutionizing the way businesses engage with their customers. Through automation, AI is reshaping customer service operations, enhancing response times, and delivering personalized solutions, all while preserving the human element.

But how can businesses harness the power of AI for customer service?

Join Ramesh Dontha and guests as they discuss:

-  The evolution of chatbots 
-  Emerging customer service AI tools
-  Why the human element is important in customer service, and how to preserve it when working with AI models
-  And much more!

AI in Customer Service: Chatbots and Beyond

AI presents exciting business opportunities and advancements, but it's essential to address the ethical challenges it brings, especially in detecting and mitigating bias within machine learning models.

Join us in this session as we discuss:

-  Fairness, accountability, and transparency in AI systems
-  Real-world case studies where bias has had serious consequences
-  How businesses can responsibly use AI while ensuring ethical guidelines are followed

This session aims to equip you with the knowledge and tools needed to navigate the ethical landscape of AI, ensuring that your use of this technology is both innovative and responsible.

AI and Ethics: Navigating Bias and Fairness in Machine Learning

Artificial intelligence and Machine learning (AI/ML) is a hot topic in every business at the moment, and there is a growing dialog about what constitutes an Open Model, is it the weights? Is it the data?

Those are important questions, but equally important is ensuring that the tooling and frameworks to train, validate, fine-tune, and perform inference are open source. Storage systems are a crucial component of these workflows, how can open-source solutions address the needs for high capacity and high performance?

Data is key to any and all AI/ML workflows, without it there would be no data to use as an input for model training, re-evaluation and refinement of models, or even just securely storing models once training is complete, especially if they have taken weeks to produce!

Open source solutions like Ceph can provide almost limitless scaling capabilities, both for performance and capacity. In this webinar, learn how Ceph can be used as the backing store for AI/ML workloads.
We’ll cover:
• The demands of AI on storage systems
• How open source Ceph storage fits into the picture
• How to approach Ceph cluster scaling to meet AI’s needs
• How to get started with Ceph

Ceph Storage in a World of AI/ML Workloads

In the first episode of the year, join Ramesh Dontha and guests as they deep dive into trends, predictions and insights into what 2025 will bring to the AI landscape -- from new technologies to new opportunities for innovation.

Shaping Tomorrow: Key AI Trends and Innovations to Watch for in 2025

Join is in the final episode of the year as Ramesh Dontha and guests deep dive into the key trends in AI from 2024, and what to expect as we move into 2025.

A Year in Review: How Did AI Change the Playing Field in 2024?

Join us for an insightful webinar on the transformative impact of AI on networking. This session will delve into the various use cases of AI, the nature of traffic for different workloads, and the network impact of these workloads. We will explore the multiple networking challenges posed by AI and how Ethernet is evolving to meet these demands. Special focus will be given to congestion issues during model training, the role of Ultra Ethernet Consortium (UEC), and the specific requirements related to training large language models (LLMs) and other use cases.

Learning Objectives:
- Understand the different types of Network Topologies typically used with AI workloads.
- Identify the nature of traffic for various AI workloads and their impact on networks.
- Learn about the challenges Ethernet faces with AI workloads and the solutions being implemented.
- Explore a specific use case to see how Ethernet addresses bandwidth and congestion issues.

Don’t miss this opportunity to stay ahead in the rapidly evolving field of AI and networking. Register now to secure your spot and gain valuable insights from industry experts!

Ethernet in the Age of AI: Adapting to New Networking Challenges

AI represents real value for business growth, internal optimization, and cost efficiency - but implementation is not always an easy task. 

Join Ramesh Dontha and guests as we discuss:
-  The most common obstacles faced by businesses when creating and enforcing an AI strategy
-  How to navigate these challenges for business success
-  Tackling resistance to your AI strategy

Challenges in AI Implementation: Overcoming Obstacles and Resistance

This presentation examines the critical role of storage solutions in optimizing AI workloads, with a primary focus on storage-intensive AI training workloads. We will highlight how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms. We will explore how AI frameworks like PyTorch utilize different storage connectors to access various storage solutions. Finally, the presentation will delve into the use of file-based storage and object storage in the context of AI training: 
 
Attendees will:
- Gain a clear understanding of the critical role of storage in AI model training workloads
 - Understand how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms
- Learn how AI frameworks like PyTorch use different storage connectors to access various storage solutions.
- Explore how file-based storage and object storage is used in AI training

The Critical Role of Storage in Optimizing AI Training Workloads

AI adoption differs significantly across industries, countries and even continents. Join us in this session as Ramesh Dontha and guests deep dive into the different applications of AI on a global scale.

The Global Impact of AI: Differences in Adoption & Application Across Continents

How can AI advance and innovate your marketing campaigns? Join Ramesh Dontha and guests in our 47th episode as we deep dive into the potential of AI in marketing, and why AI should be in every marketer's tool box.

AI and Personalized Marketing: Engaging the Modern Consumer

Join Ramesh Dontha and guests in the 45th episode of AI: The Future of Business as we deep dive into deep learning, what it means for businesses, and how to leverage its full potential.

Deep Learning Explained: Its Impact and Future Potential

As concerns about the environment rise, and we begin to really feel the impact of global warming - AI presents itself as an unexpected but promising tool in the fight against climate change. AI within sustainability is now charting new pathways to monitor, analyze, and address environmental challenges. Forecasts suggest that by 2027, AI-driven environmental solutions will significantly impact carbon footprints, waste management, and conservation efforts on a global scale. 

AI technologies are empowering organizations to monitor environmental changes in real-time, predict ecological trends, and even optimize resource consumption. From satellite imagery analyzing deforestation rates to AI-driven waste sorting and recycling, the applications are both diverse and impactful. Join us in this talk as we delve into: - The innovative approaches in which AI aids in environmental conservation - Case studies depicting AI driving sustainability initiatives across various industries - The overarching challenges and potential pitfalls of intertwining AI with ecological efforts

Join us in this webinar as we discuss:

-  How AI is helping with real-time monitoring of environmental changes
-  How AI is predicting the ecological changes
-  Optimize resource consumption with AI
-  Case studies of AI-driven environmental conservation
-  And much more!

AI in Environmental Conservation and Resource Optimization

The financial landscape is being reshaped at an unprecedented rate, with AI sitting at the centre of this transformation. From automating mundane tasks to predicting market trends, AI's influence on the finance sector is both profound and multifaceted. Experts predict that by 2028, the vast majority of banking, investment, and insurance processes will be either assisted or entirely driven by AI technologies. In this rapidly evolving landscape, AI enables risk assessments with greater precision, facilitates personalized banking experiences, and even optimizes investment and lending portfolios using real-time data analytics. The shift isn't just about efficiency but also about creating new financial products and services that were previously unimaginable. Yet, despite the rising activities, recent regulatory changes and advancements in AI created the perfect storm for risk management practices in financial services to adapt and evolve.

Join us in this webinar as we discuss: 
- Top AI trends in finance
 - Real life examples highlighting the transformative impact of AI on financial institutions 
- The ethical and regulatory challenges posed by the integration of AI in finance 
- And much more!

 Reserve your spot now!

AI in Finance: Risk Management, Challenges and Opportunities

Education is widely impacted by the evolution of AI. As classrooms worldwide transition from traditional to technologically augmented settings, AI is becoming a top contender when it comes down to fostering personalized learning experiences. 

Projections indicate that by 2026, a significant portion of educational institutions will integrate AI tools. 

In this transformative era, AI has the capability to customize educational content, adjust pacing based on student performance, and even provide real-time feedback. Beyond the walls of the classroom, AI-driven platforms are democratizing access to quality education, bridging gaps, and fostering inclusivity.

Join us in this session as we explore:

-  The ways in which AI is revolutionizing traditional methodologies and tools
- Success stories showing institutions harnessing AI for enhanced learning outcomes
-  The future of AI in education and the challenges to its widespread adoption

The Rise of AI in Education: Personalized Learning and Beyond

The entertainment industry is undergoing a radical transformation, with AI emerging as the linchpin of this shift. Traditional media paradigms are being reshaped as AI introduces innovative ways to curate, produce, and distribute content. 

Research suggests that by 2025, the majority of content recommendation engines and personalized entertainment experiences will be driven by sophisticated AI algorithms.

AI has the potential to offer hyper-personalized content to viewers, streamline production workflows, and even generate entirely new forms of entertainment. Beyond just recommendations, think of AI-scripted movies, or music tracks fine-tuned to individual preferences. The horizon of possibilities is vast and largely unexplored.

Join us in this session as we discuss:

-  The burgeoning role of AI in content creation and distribution
-  How AI-driven analytics is reshaping audience engagement and monetization strategies
-  Navigating the challenges and ethical considerations of AI in the world of media and entertainment

AI in the Entertainment Industry: Changing the Face of Media

As Artificial Intelligence (AI) moves from experimentation to wider adoption, organizations increasingly need to make decisions on computing, storage, and networking infrastructure. These infrastructure decisions heavily depend on skill set, costs, and the degrees of adoption - and businesses have to adapt and be flexible. 

Join us for episode 4 of AI: The Future of Business, where host Ramesh Dontha and guests explore how businesses can explore AI infrastructure considerations in an agile, forward-thinking and adaptable manner. 


They’ll be discussing:
- What infrastructure is required for AI as substantial amounts of data keeping ratcheting up
- How cloud technologies - particularly hybrid cloud solutions - are and will be the foundation of AI
- Essential Make Vs. Buy decisions to ensure cost levels remain competitive
- And more

Guests:
- Dan Waters - Director of Business Development, Artificial Intelligence at Samsung SDS Americas
- Jérémie Farret - Vice President, Advanced Analytics & Artificial Intelligence at Inmind

Infrastructure for AI: Flexibility, Cost and Adaptability

Artificial Intelligence

Cloud

Cloud Analytics

Cloud Applications

Data Analytics

Data Architecture

Enterprise Cloud

Enterprise IT

Hybrid Cloud

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Infrastructure for AI: Flexibility, Cost and Adaptability

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