Aussie BroadBand on Acquisition Spree

First, what I wrote about ABB's FY23 Results last year.   

Update on ABB's Business 

ABB's Acquisition Spree - Ongoing Tussle and Drivers Behind it. 

My other post on NBN and its Economics

Australias Telecom Industry in Transition

Australia Telecom Industry in Transition - From Four Pillar to Six Pillar Model 

Australia Telecom Industry - Fixed Services 

Australia Telecom Industry - Fixed Internet Ranking  

Australia Telecom Industry - Mobile Services 

Australia Telecom Industry - Mobile Internet Ranking  

My previous post on the Global Telecom Industry Evolution to date.

Generative AI - Where is The Growth ?

 Generative AI - Where is The Growth? 

• The current state of the Gen AI industry shows that big tech companies, especially hyper scalers, dominate the scene. They are the primary drivers of innovation and growth, focused on achieving long-term sustainability by shifting their focus from selling computing to selling generic and specialised model services with higher margins. 
• This has led to increased interest from venture capitalists, resulting in numerous startups focused on selling model-based services and integrating with existing apps and services. The low barriers to entry make it easy for startups to grow in the short term, but sustainability is challenging without a unique proposition. Many startups will likely fail, with some being acquired by larger companies.
•  Software providers such as Salesforce, Oracle, and Workday are also integrating AI services, either by building or purchasing specialised services to defend and survive the industry changes.

Future of Language Models

• Large Language Models (LLMs) are incredibly resource-hungry (compute & finance), making them only accessible to a select few organisations. Besides their time to market duration is not desirable.
• Google, Meta, and other major players in the AI industry are actively working to make LLMs more efficient and affordable for wider 

Foundation Model vs Large Language Model

Large Language models (LLMs) are a type of machine learning model that can process and generate human language. They are trained on massive datasets of text and code and can be used for a variety of tasks, such as translation, summarisation, question answering, and creative writing.

Foundation Models are a newer type of AI model that is still under development. They are trained on even larger datasets of text, code, and other types of data, such as images and videos. Foundation models are designed to be more general-purpose and adaptable than LLMs, meaning that they can be used for a wider range of tasks.

Key Differences

Foundation models are multimodal, meaning that they can work with multiple types of data. This enables them to perform tasks that would not be possible for an LLM alone, such as generating images from text or translating videos between languages.

Besides, Foundation models are designed to be more transferable. This means that they can be easily adapted to new tasks without having to be retrained from scratch. This makes them more practical for use in real-world applications.

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

• AI Value Chain 
• 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, Nvidia, Google, AWS, Fourweek MBA Blog, Amazon, Ashwath Damodaran, TSMC

Generative AI - Framework to Identify Use Case and Investment

 Generative AI - Framework to Identify Use Case and Investment

Application of Framework - Use Cases for Telecom

Gen AI - Use Cases for Telecom

Palo Alto Networks - What is their Growth Template

Palo Alto Networks - Leader in Cyber Security  

Key Indicators 

• Market Cap – 73.07 Bn
• EV – 72.95 Bn
• Debt - $2.26Bn
• P/B – 41.79 (Goodwill from M&A) 
• P/E (Trailing) – 184.99 (Growth) 
• P/E (Forward) – 44.44 (Growth)
• Economic Moat: Wide (product, innovative)   

• Palo Alto Network provides network security solutions. The company's solution offerings spread across network security, cloud-native application protection, security operations, and endpoint security and are available across multiple key industries.
• Cybersecurity has 5 stage lifecycle - Identify, Protect, Detect, Recover and Restore. This cyclical process is essential for protecting an organisation from cyber threats. It helps to ensure that corporations are constantly prepared and able to respond to evolving threats.

Dominating Growth Strategy

Since Nikesh Joined as CEO in 2018, Palo Alto Networks has grown with a CAGR of 24.9% with market cap. surging by $48Bn to $73.1Bn. This growth is spurred by M&A activity, improving the top line and ensuring it outpaces both competitors and potential security threats from hackers.

Palo Alto Networks has spent nearly $4Bn in acquiring 17 businesses, to form its Cortex and Prisma Cloud businesses, since its inception. The company has consistently demonstrated its commitment to driving integrated organic growth through mergers, acquisitions, and partnerships with several well-known startups. Time and again, the company has proven its capability to integrate these acquisitions to enhance or complement its own product offering.

There are various activities taking place beneath the surface, including incoming acquisitions through M&As and partnerships, as well as ongoing spin-offs initiated by former employees. The company boasts of notable start-ups that have been founded by its alumni. 

The company strives to stay ahead of the competition by promoting a start-up culture internally and keeping a close watch externally for any potential opportunities. In the future, with Gen AI coming onto the centre stage it will focus on an AI and ML-centric acquisition that will have applications in cyber security.

The strategy of acquiring small and nimble players to ensure cutting-edge technology is available to its customers has proven effective. Nikesh, who has previously worked at Google, has adopted the same playbook from his former employer. However, due to the rise in short-term debt, the company's ability to generate FCF has decreased, making it difficult to pursue any big deals.

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

• AI Value Chain 
• 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, Nvidia, Google, AWS, Fourweek MBA Blog, Amazon, Ashwath Damodaran, TSMC

IBM a Tech Giant - How it Lost its Way

 IBM a Tech Giant - How it Lost its Way

Key Indicators 

• Market Cap – $129.39Bn
• EV – $173.4Bn
• Debt - $57.5Bn, Cash - $17.9Bn 
• P/B – 8.57 
• P/E (Trailing) – 60.44 (Growth) 
• P/E (Forward) – 14.3 (Div. Centric,  No Growth)
• Economic Moat: Narrow (under threat)  

Where is the Growth

How it Lost its Way

• IBM a more than 100-year-old company that used to be a trendsetter in the technology space has become a laggard and is struggling to get its Mojo back. It is facing headwinds, and it is not clear how it will modernise its business. Today, IBM has 3 business segments, Infrastructure, Software and Consulting, and all of them are declining YoY. There are multiple reasons why IBM's revenues are declining except for the minor surge in 2021, and 2022. Let's look at the key reasons.
• Unlike its peer group players like Salesforce and ServiceNow which specialises in providing packaged application software in the Cloud (SaaS), IBM has no application software to offer. Instead, IBM's software offering is primarily in system software, such as middleware, database management systems, and operating systems, that are used to build applications, but it has no end-user applications to offer. To add further, the issue with IBM's system software business is that it is increasingly moving towards open-source software, like how its other peer, Oracle is facing headwinds in the Database domain. IBM's Red Hat Enterprise Linux is built on open source and is cheaper than the company's legacy proprietary software. 
  
• Microsoft, it's another peer, that competes with IBM in the Enterprise IT, has developed a mousetrap around Windows OS and its MS Office offering for both consumers and businesses. IBM, on the other hand, has no such product. Its other distant peer group players like Google and Meta, unlike IBM, earn most of its revenue from advertising.
• The IT spending in OPEX has been flat since the augment of Digital Transformation in the early 2010s. Most of the IT spending is CAPEX-centric for corporates to transform their businesses by rolling out customer-centric applications in the cloud and reducing the spending on system upgrades like Mainframes. In a way, the IT spending profile has significantly changed from being OPEX and IT-centric to CAPEX and business-driven. To add further, the Cloud first approach by businesses got a boost during the pandemic for resiliency and agility, ensuring that the likes of AWS and Microsoft extended their market share. In comparison, IBM has been relegated to a Cloud Consulting business where they help implement AWS, Azure and Google Cloud for their clients. This change is validated by IBM's Cloud market share decline from 25% in 2016 to 4% in 2022, indicating a lack of success in its effort to be a major player in this segment.
• IBM ventured into the AI industry during the early 2010s, introducing its Watson platform. However, the platform's performance was lacklustre, resulting in IBM selling its Watson Health initiative at a significant loss. The company is now making a fresh push into the market by relaunching Watson with the new name of watsonx, keeping in mind the current trend of Generation AI. IBM had previously rebranded its flagship database from DB2 to Db2 to rejuvenate it, but the move led to its downfall, especially among developers. IBM is now attempting a similar strategy with its AI offerings. It remains to be seen, whether rebranding will help IBM boost its AI efforts and achieve much-needed growth.
• During the mid-1990s, IBM decided to shift its focus from hardware manufacturing to the IT Managed Infrastructure Services sector, to drive growth in its software and consulting businesses by moving up the value chain. This strategic transition was necessary to meet the changing needs of customers who were moving away from mainframes and towards commodity hardware-enabled servers. However, in recent years, the IT Managed Infrastructure Services industry has experienced a decline due to the emergence of Hyperscalers and a change in IT spending. Today, most of IBM's original mainframe customers have shifted to the cloud or on-premise commodity hardware platforms for new application development, adding to the company's current challenge of finding ways to drive growth.
• IBM's IT Consulting segment has maintained a steady performance, with operating margins staying flat at 10-12%. The company has been pushed by market forces to shift its focus from providing consulting services solely based on its products to helping clients implement software from other companies. This shift is similar to the approach of a System Integrator. Despite IBM's attempt to emulate the cost arbitrage model of the leading Indian SI players, it has not been successful. Additionally, the margins in the consulting business have decreased, whereas the software business provides healthy margins due to the negligible marginal cost of selling an additional unit.
• To summarise, It's unsurprising that IBM is undervalued in comparison to its peers, given the various aspects that have been discussed. Wall Street analysts view IBM as a dividend stock with limited potential for capital growth, which is reflected in its forward PE of 14 and the market cap of $129Bn only, 18 times less than Microsoft's market cap of $2.4Tn.

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

• AI Value Chain 
• 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
• 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

Generative AI - Changing the World, Key Players and Their Progress

 Generative AI - Changing the World, Key Players and Their Progress - Part One