Oracle's Evolution - Database Leader to AI Innovator

 Oracle's Evolution - Database Leader to AI Innovator  

• Market Cap – 290.15 Bn
• EV – 369.18Bn
• Debt - $88.94Bn (High), Cash – $12.08Bn 
• P/B – 122.43 (intangibles in the book) 
• P/E (Trailing) – 31.05 (Growth) 
• P/E (Forward) – 19.43 (Growth)
• Economic Moat: Wide (product sales, under threat)   
• Domain: Enterprise Software and Database
• Comp. (Business Apps) – IBM, SAP, Workday, MSFT, Salesforce
• Comp. (Database) – MongoDB, MySQL, Cassandra, AWS, Azure, IBM 
• Growth Segment – OCI (Up) 

Oracle's Facing Headwinds - In the Age of No SQL

The emergence of Digital Transformation in the early 2010s has brought multiple challenges to Oracle's relational database segment.

Today, it is facing stiff competition from both commercial and open-source vendors. It must constantly innovate and create new products and services to stay ahead of the database market. Despite the challenges, it is rising to the occasion by developing its own cloud-native database products and investing in artificial intelligence and machine learning to enhance the intelligence and autonomy of its databases.

Oracle  - Where is the Growth

Oracle  Nvidia Partnerhip

 

Oracle's Gen AI Play - Partnership With Cohere 

Oracle, a major player in the technology industry, has been comparatively late in adopting the latest advancements in Gen AI, especially as compared to the major hyperscalers. However, it is now attempting to make up for the lost time by partnering with Cohere (LLM provider), while also leveraging its strong relationship with Nvidia, a global leader in the GPUs. This strategic move is expected to enable Oracle to enhance its AI capabilities and remain competitive in the market.

My other posts on Generative AI and Strategic Analysis of Key Players

• AI Value Chain 
• TSMC - The Chipmaker That Runs The World
• Amazon the King of Retail -WhyAWS is the Crown Jewel
• Microsoft the King of AI in Software, Salesforce under the AI Cloud 
• Tesla - It's not a Car, Its an AI Device on Wheels
• Google the King of Search - What the Future Beholds in the AI World
• Nvidia Godfather of AI - Why the Market is Bullish
• Generative AI can transform Telecoms, Energy and Utilities

Source: SeekingAlpha, Bloomberg, Martinfowler.com, Databricks.com, Nvidia, Google, AWS, Fourweek MBA Blog, Amazon, Ashwath Damodaran, TSMC

Google the King of Search - What the Future Beholds in the AI World

Google: The King of Search - What the Future Holds in the AI World 

Google's Evolution

 

Google King of Search - Where is the Growth

Google Search - Economics with Gen AI

Google Cloud's - AI and ML Play

Googles AI Journey 

Googles $100Bn Blunder

Google - Risks to its Growth

My other posts on Generative AI and Strategic Analysis of Key Players

• AI Value Chain 
• Salesforce under the AI Cloud 
• Amazon the King of Retail -WhyAWS is the Crown Jewel
• Microsoft the King of AI in Software, Salesforce under the AI Cloud 
• Tesla - It's not a Car, It's an AI Device on Wheels
• Google the King of Search - What the Future Beholds in the AI World
• Nvidia Godfather of AI - Why the Market is Bullish
• IBM - How it Lost Its Way
• Generative AI can transform Telecoms, Energy and Utilities

Source: Seekingalpha, Bloomberg, Martinfowler.com, Databricks.com, Linkedin, Nvidia, Google, AWS, Fourweek MBA Blog, Amazon

Amazon Flywheel Phenomenon - AWS is The Crown Jewel

Amazon Flywheel Phenomenon - Why AWS is The Crown Jewel 

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Amazon Evolution

 

Where is the Growth

 

Amazons Flywheel Phenomenon

Amazons Multiple Flywheels 

AWS The Crown Jewel 

Amazon Chasing new Flywheel

My other posts on Generative AI and Strategic Analysis of Key Players

• AI Value Chain 
• Microsoft the King of AI in Software, Salesforce under the AI Cloud 
• Tesla - It's not a Car, Its an AI Device on Wheels
• Google the King of Search - What the Future Beholds in the AI World
• Nvidia Godfather of AI - Why the Market is Bullish
• Generative AI can transform Telecoms, Energy and Utilities

Source: SeekingAlpha, Bloomberg, Martinfowler.com, Databricks.com, Nvidia, Google, AWS, Fourweek MBA Blog, Amazon, Ashwath Damodaran, TSMC

Nvidia Godfather of AI - Why the Market is Bullish

 Nvidia Godfather of AI - Why the Market is Bullish

What is their Economic Moat

Where is the Growth

Dot Com Era - History Repeating Itself 

Nvidia - Under The Hood 

Two CEO's Personal and Professional Relationship

Risks to its Growth

My other posts on AI Value Chain,  Microsoft King of AI in Software, Salesforce under the AI Cloud, AWS is the Crown Jewel and how Generative AI can transform Telecoms, Energy and Utilities

Microsoft - The King of AI in Software and Cloud

Microsoft's transformation under Satya is phenomenal, from a PC dominant player to being called the King of AI in Software and Cloud.  

Where is the Growth

Partnership with OpenAI

Why Microsoft is called as The King of Generative AI in Software and Cloud. 

My other posts on AI Value Chain,  Microsoft The King of AI in Software, Salesforce under the AI Cloud , AWS is the Crown Jewel and how Generative AI can transform Telecoms, Energy and Utilities

Source: Seekingalpha, Bloomberg, Martinfowler.com, Databricks.com Linkedin, Nvidia, Google, AWS

CEO Leadership - Amazon, Microsoft and Googles Evolution

 Amazon, Microsoft and Google Evolution  - How these three Cloud Giants have evolved in terms of market cap and CEO leadership.

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Salesforce - Under The AI Cloud

 Salesforce - Under The AI Cloud 

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• Marc, known for his mission and marketing mantra, ”The End of Software", Revolutionised the CRM industry by introducing a Cloud-based service. 
• Despite facing tough competition from companies like Oracle, SAP, and Microsoft, it has emerged as the leader in this field. Today it commands 23% of the Global Market Share.
• Strategically acquired companies like Tableau, Slack (Data & Analytics) and MuleSoft (PaaS) to build a platform-centric flywheel by integrating CRM and Business System applications.
• With a Market Cap of US $209Bn and a Robust Economic Moat, it can become a $500Bn company by the end of this decade.

Strategic shift from Competition (MSFT 365, ORCL) to Cooperation (Google, OpenAI)

Risks to AI Ambitions

My other posts on Generative AI and Strategic Analysis of Key Players

• AI Value Chain 
• Salesforce under the AI Cloud 
• Amazon the King of Retail -WhyAWS is the Crown Jewel
• Microsoft the King of AI in Software, Salesforce under the AI Cloud 
• Tesla - It's not a Car, It's an AI Device on Wheels
• Google the King of Search - What the Future Beholds in the AI World
• Nvidia Godfather of AI - Why the Market is Bullish
• IBM - How it Lost Its Way
• Generative AI can transform Telecoms, Energy and Utilities

Source: Seekingalpha, Bloomberg, Martinfowler.com, Databricks.com Linkedin, Nvidia, Google, AWS

NVIDIA - Godfather of AI - Why the Market is Bullish

Key Message

• Q2 FY23 -  The data centre business, driven by demand from cloud providers and internet companies, played a vital role, contributing $10.32 billion (76% of total revenue). Gaming revenue also grew positively to $2.49 billion.
• Products like the H100 tensor core GPU, DGX supercomputers, inference platforms, and AI Infrastructure-as-a-Service in the cloud are poised to transform AI delivery, partnered with major cloud providers.
• Today, Nvidia commands 70% of the AI Chip market.
• Other Key players are AMD, ARM (Softbank) and Intel.

Where is the Spend

If you take the other Nvidia divisions, separate them out and add them together, revenues were up by 9.9% to $3.18Bn. That’s another way of saying that the Nvidia datacentre business is now 3.2x bigger than the rest of Nvidia, and the datacentre business now accounts for 76.4% of the overall sales for the company.

What is their Economic Moat

A single chip can cost upwards of US$40K, and OpenAI used about 10,000 of them to train ChatGPT. If you want to train a GPT5-level model, you apparently need somewhere on the order of 20K to 25K H100 GPU accelerators, and that is somewhere around two dozen $1 billion machines

Nvidia's Economic Moat is driven by its 1st mover advantage in the AI Chip segment, supported by the network effects of a multisided platform and a frictionless Flywheel.

Nvidia's Economic Moat is driven by its 1st mover advantage in the AI Chip segment, supported by the network effects of a multisided platform and a frictionless Flywheel.  

My other posts on AI Value Chain and how Generative AI can transform Telecoms, Energy and Utilities

Source: Seekingalpha, Bloomberg, Martinfowler.com, Databricks.com Linkedin, Nvidia, Google, AWS

Why Amazon Web Services (AWS) is a leader in Cloud Computing

Why Amazon Web Services (AWS) is a leader in cloud computing?

Response from ChatGPT (Generative AI Tool)

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Amazon Web Services (AWS) is considered a leader in cloud computing for several reasons, which have contributed to its dominant position in the cloud services market: 

• Comprehensive Service Portfolio: AWS offers a wide range of cloud services, including computing, storage, databases, machine learning, analytics, IoT, security, and more. This extensive portfolio enables organizations to address diverse business needs within a single cloud provider.
• Global Reach: AWS has a global presence with data centres (Availability Zones) in multiple regions around the world. This global network infrastructure allows customers to deploy their applications and services close to their end-users for low-latency access.
• Scalability and Elasticity: AWS provides scalable and elastic infrastructure, allowing users to easily adjust resources up or down based on demand. This pay-as-you-go model is cost-effective and flexible for businesses of all sizes.
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  Reliability and Availability: AWS has a track record of high availability and uptime. It offers robust service-level agreements (SLAs) for many of its services, and its global network is designed for redundancy and fault tolerance. 
• Security and Compliance: AWS places a strong emphasis on security and compliance. It offers a wide range of security tools and services, and its data centres meet rigorous security standards. AWS also provides compliance certifications for various industries and regions.
• Innovation and Technology Leadership: AWS is known for continually innovating and launching new services and features. It invests heavily in research and development, staying at the forefront of emerging technologies like machine learning, artificial intelligence, and serverless computing.
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  Ecosystem and Partnerships: AWS has a vast ecosystem of partners, third-party integrations, and a vibrant developer community. This ecosystem supports a wide variety of use cases and enables customers to access additional tools and services.
• Cost Management: AWS provides cost management tools and features, such as AWS Cost Explorer and AWS Budgets, to help customers optimize their cloud spending and control costs.
  
• Customer Focus: AWS has a customer-centric approach, with a dedicated support team and resources to assist customers with their cloud initiatives. This focus on customer satisfaction has helped build strong relationships with organizations across industries.
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  Hybrid and Multi-Cloud Capabilities: AWS offers solutions for hybrid cloud deployments, allowing customers to seamlessly integrate their on-premises infrastructure with AWS services. Additionally, AWS provides services for multi-cloud management and deployment.
• Educational Resources: AWS provides extensive documentation, training programs, and certification opportunities to help individuals and organizations build cloud skills and expertise.
• Market Leadership and Experience: AWS entered the cloud computing market early and has accumulated years of experience. This leadership position has allowed AWS to refine its services and infrastructure continually.

AWS's combination of technical excellence, a broad and deep service offering, a global presence, and a strong focus on customer success has positioned it as a leader in cloud computing, serving a diverse customer base that includes startups, enterprises, government agencies, and nonprofits.

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My previous post on the following Cloud Topics

• Cloud Benefits and Risks
• Distributed Cloud Battle - AWS vs Google
• Evolution of Cloud Migration Strategy for IT and Business Application 
• Post COVID - Why Digital and Cloud is on Fire
• Sales Trigger Spectrum with Cloud Adoption Curve - 2022

How Generative AI Can Transform Communication Service Providers

How Generative AI Can Transform Communication Service Providers (CSPs) 

The global generative AI in telecom market size was at US $150.81Mn in 2022 and it is expected to rise to US $4.9Bn by 2032, with a CAGR of 41% from 2023 to 2032.

Response from GenAI tool: 

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Generative AI has the potential to transform Communication Service Providers (CSPs) in several ways, enabling them to enhance their services, improve operational efficiency, and stay competitive in a rapidly evolving industry. Here are some key ways generative AI can drive transformation for CSPs:

• Enhanced Customer Experiences: Generative AI can be used to create highly personalised customer experiences. Chatbots and virtual assistants powered by generative models can provide 24/7 customer support, answer queries, and offer personalized recommendations, improving overall customer satisfaction.
  
  
  
• Natural Language Processing (NLP): Generative AI models can process and understand natural language, allowing CSPs to offer advanced NLP-based services. This includes sentiment analysis, language translation, and voice recognition, enhancing customer interactions and support.
• Content Creation and Recommendations: Generative AI can automate content creation for marketing and customer engagement. It can generate text, images, and videos, and offer content recommendations based on customer preferences, increasing engagement and revenue opportunities.
• Predictive Analytics: Generative AI can analyse vast amounts of historical data to predict network outages, service disruptions, and customer churn. This enables CSPs to proactively address issues, improve network reliability, and reduce customer attrition.
• Network Optimisation: CSPs can use generative AI to optimise network configurations, allocate resources efficiently, and enhance network performance. Predictive modelling can help with traffic management and capacity planning.
• Fraud Detection and Prevention: Generative AI can detect and prevent fraud in real time by analysing call records, transaction data, and network traffic. This minimizes financial losses and ensures network security.
• Data Monetisation: CSPs can monetise the vast amount of data they generate by offering data analytics and insights services to businesses. Generative AI can create valuable data-driven reports and recommendations for corporate clients.
• IoT and Smart Services: Generative AI can facilitate the growth of IoT services by optimising data processing and analytics for connected devices. CSPs can offer end-to-end IoT solutions for various industries, including smart cities, healthcare, and manufacturing.
• Voice and Video Quality Enhancement: Generative AI can be used to improve the quality of voice and video communications by generating missing data, reducing noise, and optimising network performance, leading to a better user experience.
• Cost Reduction and Automation: Generative AI can automate repetitive and time-consuming tasks, reducing operational costs and increasing efficiency in areas such as network management, customer support, and billing processes.
• Service Expansion and Innovation: With generative AI, CSPs can explore innovative service offerings in emerging areas such as 5G, edge computing, and augmented reality (AR)/virtual reality (VR) services, tapping into new revenue streams.
• Market Differentiation: Embracing generative AI can help CSPs differentiate themselves in a competitive market by offering unique and innovative services that cater to evolving customer demands.
• Cybersecurity: Generative AI can be used to strengthen network security by identifying and mitigating potential threats in real-time, and safeguarding sensitive customer data and network infrastructure.

By leveraging generative AI technologies, CSPs can not only transform their operations but also create new revenue opportunities, improve customer satisfaction, and position themselves as leaders in a rapidly evolving telecommunications landscape.

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My previous post on Generative AI Value Chain

Why Telcos are Struggling for ROI

Why Telcos are Struggling for ROI 

Response from GenAI Tool

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The telecom sector has faced several challenges that have made it difficult to generate a satisfactory return on investment (ROI). While these challenges can vary by region and market conditions, here are some key factors contributing to the struggles of the telecom sector in generating ROI:

• High Infrastructure Costs: Building and maintaining the physical infrastructure for telecommunications networks, including towers, fibre optics, and data centres, requires substantial capital investment. The initial costs of rolling out networks and keeping them up-to-date can be burdensome.
• Intense Competition: Telecom markets are often highly competitive, with multiple providers vying for the same customer base. This competition can lead to price wars, reduced profit margins, and increased spending on marketing and customer retention.
• Regulation and Compliance: The telecom industry is subject to complex and evolving regulatory frameworks, which can vary significantly from one region to another. Complying with regulations and licensing requirements can be costly and time-consuming.
• Technological Advancements: The rapid pace of technological change in the telecom sector means that companies must continually invest in upgrading their networks and services to remain competitive. This ongoing investment can strain profitability.
• Market Saturation: In many mature markets, the number of potential new customers has plateaued, making it challenging to expand the customer base. Telecom providers must focus on retaining existing customers and increasing revenue per user (ARPU).
• Shift to Data Services: With the increasing demand for data services, telecom companies have had to invest heavily in expanding their data networks & upgrading infra. to support the growth in data usage. This can be costly, & monetising data services can be complex.
• Rising Customer Expectations: Consumers and businesses expect high-quality, high-speed connectivity and a wide range of services. Meeting these expectations often requires continuous investment in improving network performance and service offerings.
• Debt and Capital Structure: Telecom companies often carry significant debt loads due to the need for extensive infrastructure investments. High levels of debt can lead to interest expenses that eat into profitability.
• Emerging Technologies: Emerging technologies like 5G, edge computing, and the Internet of Things (IoT) require substantial investment but may take time to yield significant returns. Companies must carefully balance these investments with revenue expectations.
• Over-the-Top (OTT) Services: OTT services like messaging and video streaming apps have disrupted traditional telecom revenue streams. These services often bypass traditional revenue channels like SMS and voice calls.
• Customer Churn: High customer churn rates can erode revenue as companies need to continuously acquire new customers to replace those lost. Improving customer retention can be more cost-effective than customer acquisition.

To overcome these challenges and improve ROI, telecom companies often focus on strategies such as diversifying service offerings, optimizing network efficiency, reducing operational costs, and exploring new revenue streams through partnerships and innovative services. Adapting to changing market dynamics and customer demands is crucial for long-term success in the telecom sector.

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