Well, things aren't going so well on the markets at the moment. I wavered a little as to whether I should wait and see or perhaps use the correction in "tech" to buy more ($NVDA (-4,37 %) , $QCOM (-4,52 %)).

Since I couldn't make up my mind, it was once again the $CSPX (-2,87 %) ...

Dividend at 2.15% and will be reduced to 0.89$ from June. 22 year in a row at approx.30% payout.

In addition, the company is busy buying back its own shares, in the last quarter alonel 11 million shares for 1.8 billion dollars

The latest earnings

Source

https://www.qualcomm.com/news/releases/2025/03/qualcomm-increases-quarterly-cash-dividend

https://s204.q4cdn.com/645488518/files/doc_financials/2025/q1/FY2025-1st-Quarter-Earnings-Release.pdf

$QCOM (-4,52 %)

Qualcomm presented a new brand today, before the start of MWC 2025 in Barcelona: Dragonwing. From now on, Dragonwing will act as an umbrella brand for various solutions for business customers. That's right, you probably won't come into contact with it as a private customer. According to the manufacturer, however, the new brand is intended to take account of current market developments and increasing product categories that require a clear name.

Dragonwing will therefore function as a brand for technical solutions that can be used in industrial robots, cameras, drones and more. The brand will therefore stand for industrial and embedded IoT (Internet of Things) solutions. Qualcomm also intends to combine products for the network sector and mobile communications infrastructure under this umbrella. Custom hardware and software are to work together. There will be different, scalable solutions for companies. AI will also be included.

However, Qualcomm has not yet pulled any concrete Dragonwing brand products out of its hat. However, you can already see that they want to position the brand as broadly as Snapdragon. For example, in addition to SoCs for mobile devices, the Snapdragon brand also includes chips for vehicles, headphones and more. Dragonwing will also be positioned quite broadly as an umbrella brand for various solutions and industries.

https://stadt-bremerhaven.de/qualcomm-stellt-seine-neue-marke-dragonwing-vor/

$KTN (-5,98 %) Today I would like to introduce you to Kontron in a little more detail, as an interesting zone has been reached both fundamentally and in the chart.

Roughly speaking, Kontron is a full-stack provider (hardware and software) of IoT solutions.

Trends that Kontron plays on:

• IoT
• Industry 4.0 (i.e. networked production machines)
• automation
• Transportation (IoT data networking for trains)
• Defense (especially secure communication solutions)
• Energy and smart home (AI could also be seen here)

With KontronOS, Kontron offers a secure IoT operating system that has been specially developed for machines.

KontronGrid allows up to one million IoT devices to be connected with each other.

Last year, Kontron acquired the Katek Group, adding smart home applications and intelligent energy control (e-cars, photovoltaics) to its portfolio.

Kontron generates the majority of its sales (over 80%) in Europe and the rest mainly in the USA and China. European sales are growing significantly faster.

Summary/investment thesis:

Kontron is a very broadly positioned industrial group that manufactures and services networked technologies for production, defense and energy (AI was also mentioned here at one point). There is an ever-increasing proportion of software, which is slowly increasing margins (gross margin is now around 36-40%).

Kontron has been able to announce new orders in recent months (and also today):

• with automotive manufacturers for 5G communication modules for vehicle networking (volume approx. €250m)
• in the defense sector for high-performance communication computing units for surveillance (volume approx. 165M€)
• in the area of defense for sensors for autonomous air traffic control (20M€)
• in the area of transportation for an innovative platform for interlocking systems

There is also a collaboration with Qualcomm $QCOM (-4,52 %) to revolutionize the areas of edge computing and artificial intelligence.

The order backlog is growing steadily and the company is really playing on almost every trend. According to its own statements, there are high barriers to entry.

Here is the CEO's comment:

"Kontron has become the global technology leader of IoT technologies. With our secure KontronOS operating system, innovative solutions for ultra-fast 5G data communication and our de facto IoT standards for special markets such as railroad technology, defense and smart charging technology, we are driving future applications such as artificial intelligence - based on huge amounts of data that only IoT-enabled devices can deliver. We are therefore only at the beginning of a promising growth cycle in IoT technology."

Kontron is currently valued relatively favorably with a P/E ratio of 14.5 and a forward P/E ratio of 11 (5-year average: 19). Sales growth over the next few years is expected to be around 10%, while profits are expected to grow by 20%pa. The stock has not made a great return so far and is moving sideways, but it has risen quite a bit in the last few months. There is a resistance at around 22-22.5€ which has been tested several times (and is also ATH). There is also a dividend yield of 3.2%. The dividend should also continue to grow strongly.

PS: Kontron is sitting on a huge treasure trove of data (from all the IoT machines etc.). This could be leveraged and AI could also be used here, e.g. for digital twins or to optimize production, similar to what $SIE (-5,46 %) Siemens is currently doing

$AMD (-4,57 %)

Insider buys shares worth 500,000 at the

It's the first time an AMD insider has bought shares since Lisa Su in 2012

As legendary investor Peter Lynch says:

"Insiders sell their shares for all sorts of reasons, but buy them for one: they think the price will go up. ✌️🚀

$NVDA (-4,37 %)
$AVGO (-5,15 %)
$QCOM (-4,52 %)
$ASML (-1,43 %)
$TSM (-5,38 %)

Building on my post from yesterday....

(https://getqu.in/xnw3fe/)

in this post I would like to write more about the transition from AI infrastructure expansion to the inference market, taking into account my personal assessment and using some sources. The stocks mentioned do not constitute investment advice. As always, the lines are intended to provide impulses to understand the potential winners of tomorrow.

In recent years and currently, a large proportion of investment has gone into building the infrastructure for artificial intelligence.

Tech giants and cloud providers have built huge data centers to enable the training phase of AI models such as GPT-4 or Gemini [1].

However, a paradigm shift is now emerging: the focus is shifting from expensive training to the inference market, i.e. the practical use and monetization of AI models, as general AI models will eventually become a "commodity".

When we say that AI is becoming a commodity, this means that artificial intelligence is increasingly becoming a standard technology that is readily available and accessible to many companies and industries, similar to electricity, the internet or cloud computing today.

Standardization and availability

• AI solutions are being standardized to such an extent that companies can use them without in-depth specialist knowledge.
• Instead of creating individually developed AI systems, companies are turning to ready-made solutions or platforms (e.g. AI models, APIs or services from companies such as OpenAI, Google or Microsoft).

Lower costs

• Economies of scale and technological advances are making AI systems cheaper and therefore affordable for more companies.
• Cloud providers such as AWS, Azure or Google Cloud offer AI tools as pay-as-you-go services, which lowers the barriers to entry for smaller companies.

Wide range of applications

• AI is used in all kinds of industries, from logistics and finance to healthcare and agriculture.
• Technologies such as image and speech processing, automated decision-making and data analysis are becoming the basis for innovation.

Loss of competitive advantages

• When AI is equally available to all companies, those that used to be leaders will lose their unique competitive advantage.
• The difference will no longer lie in the use of AI itself, but in the efficient and creative application of the technology.

Long-term significance

• AI as a commodity will lead to a democratization of technology where every company has access to the same basic tools.
• Competition will shift to who uses AI better, rather than who owns or develops it.
• At the same time, new differentiators could emerge, such as industry-specific customization or unique data.

In practice, this means that AI is no longer the exclusive domain of tech giants, but a tool that anyone can use to drive innovation.

📈 Why the shift to the inference market is inevitable

From training to inference: What's the difference?

Training:

AI models are trained with enormous amounts of data, a computationally intensive process that requires specialized hardware such as GPUs and TPUs. Companies such as Nvidia, AMD and Broadcom are benefiting greatly from the boom in data centers at this stage.

Inference:

Once training is complete, the models must be used in the real world, whether through chatbots, voice assistants or image processing. Efficiency is key here, as AI has to respond to millions of requests in real time.

Capital shift: the money follows the monetization

Infrastructure development completed:

Building training infrastructure is costly, but after a certain phase, the focus shifts to optimization and more efficient use over frugal training or specialized chips.

Energy efficiency and cost optimization:

Companies are looking for solutions that are not only powerful but also energy-efficient and cost-effective, a crucial factor in maximizing margins.

🔮 The growth market of the future

The inference market is expanding rapidly as AI applications penetrate more and more areas of life and work:

Automated customer service:

Chatbots and virtual assistants are replacing traditional call centers and offer round-the-clock support (e.g. IBM watsonx Assistant) [2].

Medical diagnostics:

AI-supported image analyses improve diagnostics and enable personalized therapies [3].

Language models & generative AI:

Applications such as ChatGPT or Google Bard are revolutionizing the field of generative AI.

Industry 4.0 & automation:

Smart factories and predictive maintenance increase efficiency in production [4].

🏆 The profiteers of the inference market - how are the Big Techs positioned?

📌 AMD
$AMD (-4,57 %) Nvidia's challenger in the inference sector

Technology:

• AMD's MI300X is considered a direct competitor to Nvidia's H100 and offers advantages in terms of energy efficiency and costs [5].

Market outlook:

• With a strong positioning in the cloud and data center sector, AMD could gain market share in the growing inferencing market

Nvidia $NVDA (-4,37 %) From training king to inference king?

Dominance in the training market:

• Nvidia has dominated the training sector to date with its A100 and H100 GPUs [6].

Switch to inference mode:

• With new software optimizations such as TensorRT and specialized hardware solutions such as the Grace Hopper superchips, Nvidia is preparing to be a leader in the inference sector as well.

Google
$GOOGL (-2,76 %) TPUs as the inference solution of the future

Own AI chips:

• Google relies on its own Tensor Processing Units (TPUs) to reduce inference costs in the cloud [7].

Range of applications:

• Optimized inference chips play an essential role in Google Cloud as well as YouTube AI recommendations.

Amazon
$AMZN (-6,61 %) The cloud giant with its own AI hardware

Inferentia chips:

• Amazon's specially developed Inferentia chips are designed for the cost-effective operation of AI inference solutions [8].

Market penetration:

• With a steadily growing number of AWS customers using customized AI inference solutions, Amazon remains a key player in the AI sector.

Microsoft
$MSFT (-1,84 %) Profiteer through OpenAI & Azure AI

Partnership with OpenAI:

• The close cooperation with OpenAI positions Microsoft as one of the largest providers of inference solutions.

Azure AI:

• With Azure AI, Microsoft is building a powerful cloud infrastructure for generative AI.

Future developments:

• In-house AI chips could reduce dependence on external providers such as Nvidia in the long term.

Broadcom
$AVGO (-5,15 %) The "hidden champion" for inference networks

Network technology:

• Broadcom's high-speed networking technology enables the fast data processing that is critical for AI inference.

Market Leadership:

• As a leading provider of networking chips in hyperscale data centers, Broadcom benefits from the growing demand for AI-optimized solutions.

Qualcomm
$QCOM (-4,52 %) Inference on the edge market

Edge Computing:

• In addition to the cloud, inference is also needed on mobile devices and IoT systems. Qualcomm offers powerful, energy-efficient AI chips for this.

Smartphone applications:

• In particular, the use of Snapdragon AI processors in smartphones makes Qualcomm an important player in the edge sector.

🎯 Conclusion: the inference market could be the new AI gold rush

The AI boom is far from over, it's just shifting. While the expansion of infrastructure laid the foundation, the focus is now on continuous revenue from inference solutions.

• Companies that specialize in energy-efficient and high-performance inference hardware have long-term growth potential.

• Providers with their own AI solutions can benefit massively by reducing costs and improving margins.

• Companies like Broadcom provide the technological foundation for fast and reliable AI inference.

The inference market has long been a reality and is not a short-term phenomenon.

❓Which companies do you see benefiting alongside the big players?

In yesterday's post, I briefly outlined my personal portfolio breakdown on the topic of the AI revolution.

Thanks for reading! 🤝

__________

Sources:

[1]

https://datacentremagazine.com/it/gartner-why-global-it-spending-will-hit-us-5-61tn-in-2025

[2]

https://www.ibm.com/de-de/products/watsonx-assistant?utm_content=SRCWW&p1=Search&p4=43700081249081072&p5=e&p9=58700008827051052&gclsrc=aw.ds&gad_source=1&gbraid=0AAAAA-oK3j5oGHzEFRXtK5errGcJ_JurZ&gclid=CjwKCAiAnpy9BhAkEiwA-P8N4u6i5OsTL36ctZDn93JgG58kV90ckf7U6o2QKeKPSUqqwHSw3MxoaRoC2IwQAvD_BwE

[3]

https://www.mckinsey.com/featured-insights/themes/whats-next-in-ai-and-healthcare

[4] https://www.deloitte.com/de/de/issues/innovation-ai/industrie-40.html

[5] https://www.amd.com/de/products/accelerators/instinct/mi300/mi300x.html

[6]

https://www.nvidia.com/en-us/data-center/

[7]

https://cloud.google.com/tpu

[8]

https://aws.amazon.com/de/ai/machine-learning/inferentia/

$QCOM (-4,52 %)

Hello my dears, my personal opinion on the report would be. "Now that the Intel takeover rumors have died down, Qualcomm is trying to take more and more market share from Intel and perhaps even displace it. And thus perhaps to be able to take over Intel very cheaply in the end".

For the first time, chip giant Qualcomm has provided information on how widespread Windows PCs with its new ARM processors from the new Snapdragon X series, which have only been available since mid-2024, are. In the USA, it has a market share of 10 percent - in a niche market.

Qualcomm sees itself on the right track

As Qualcomm CEO Christiano Amon announced on the occasion of the announcement of the company's latest business figures, market researchers see growing market shares for the new generation of ARM-based Windows PCs. He referred to data from Circana, a company that also includes the NPD Group, which specializes in market analysis.

According to Amon's statistics, ARM-based systems with Qualcomm Snapdragon X-series processors currently account for around 10 percent of Windows laptop sales in the US in the price range above the USD 800 mark. What may not seem outstanding at first glance is actually quite an achievement at second glance.

Exact quantities remain open

It should be borne in mind that Qualcomm and its partners have only been active in the price segment north of the 800 dollar mark with the new Snapdragon laptops in recent weeks. This market includes various high-end devices, including gaming systems.

Of course, the Qualcomm boss did not provide exact figures on the number of Windows PCs with Snapdragon platforms sold worldwide or in the USA. The company is still in the early stages of development. Initially, the company focused on the consumer market and is now aiming for the business segment, according to Amon.

There are currently more than 80 PC designs with new-generation Snapdragon processors that are already on the market or are still under development. Qualcomm wants to increase this number to around 100 designs by 2026 together with its partners among PC manufacturers. At the same time, the company also sees a positive development in the adaptation of software for the new Windows PCs with ARM chips.

https://m.winfuture.de/news/148667

• $QCOM (-4,52 %) The chip manufacturer reported revenue of $11.67 billion for the first quarter of the 2025 financial year, an increase of 17% year-on-year.

• Earnings of $3.18 billion, or $2.83 per share, topped Visible Alpha's estimates.

The increase was supported by growing demand for chips in handheld devices, indicating a nascent recovery in the smartphone market.

These devices are a key driver of Qualcomm's business, as the company supplies a number of high-profile corporate customers, including China's Vivo and Xiaomi (OTC:XIACF), as well as iPhone maker Apple (NASDAQ:AAPL).

Dear friends of Getquin,

I'm usually a silent reader, but if everyone just reads, eventually there's no more reading material, is there? So today I want to share my story with you.

The beginnings:

It's hard for me to say exactly when my journey began, but I do know that I developed a fascination with money as a child. My first "investment" was when I was about 7 or 8 years old, when I bought an ounce of gold with my own pocket money. At that time, no one in my family had anything to do with investments, but I had seen it in my mother's bank when I often accompanied her there. I was fascinated by the shiny coins and wanted to know how I could have a piece myself.

Then, around the turn of the millennium, I saw my father, together with a "great" bank advisor, invest the entire family savings in the middle of the dotcom bubble. The result: a massive loss within a few months. But my mother, who was at home at the time, fought hard and was miraculously able to recoup the losses. I was about 9 or 10 years old at the time and watched her sit in front of the PC every day and look at the figures. From that moment on, I was hooked! I started using an Excel spreadsheet to track which shares I would have bought at what price and watched the performance of my fictitious investments with great interest every day after school.

The first few years:

My mother stopped day trading after about a year and went back to work. However, shares were no longer an issue for me until I was 26.

Getting into real shares:

In 2018, in the summer, as a die-hard Juventus fan, I read about an article on the transfer of CR7 and how Juventus shares went through the roof. I was there again! At that time, however, I only had a small income as a working student. My father, who had failed with his investments in the past, gave me €2,000 - and I bought Juventus shares. However, he made me promise him that I would never invest in shares again. How did the story end? The "trade" with Juventus was a success, but I had to pay taxes for the first time - and I still hate that to this day.

The first losses:

After my Juventus adventure, I began to delve deeper into the matter. I tried out recommendations from "Aktionär" and repeatedly bet on individual shares for smaller trades. It was more of a game, but I generally remained profitable - sometimes a few percent profit, sometimes a few percent loss. Thanks to the profits and additional deposits, I built up my portfolio to €18,000 until I was hit by Wirecard. In the end, I had to accept a loss of around €6,000. It was painful, but not life-threatening - and I learned a lot from this mistake. In particular, I made the mistake of constantly buying more. If I had left it at the original position of € 1,500, the loss would probably not have been so dramatic.

Don't give up:

After the Wirecard debacle, I radically rethought my strategy. I increasingly focused on conservative companies, regular dividend payers and low growth. But here, too, I realized that I was underperforming the market. So I adapted my strategy further and took a long-term approach. I have since been able to slowly recoup my losses.

The clean cut - a new start:

In the summer of 2023, I needed all my assets for a private housing project and decided to make a real "fresh start". I sold all the positions in my portfolio and only kept my ETF savings plans with TradeRepublic.

The new era:

When the housing project was completed, I wanted to build up a new portfolio with the money I had left over - and here you can see the result. My aim is to find companies that are growing strongly and have a solid moat. Dividends are nice, but not a must. My portfolio also contains defensive, boring stocks as a healthy addition. At the same time, I try to further expand my ETF positions through one-off purchases - I stopped my regular ETF savings plans at the end of January 2025. I have also invested a little in crypto and gold on the side. I have made further investments in Lego (€500), Pokémon (€1,000) and Counterstrike cases (€3,000), but these are not part of the public list - that would be too costly for me.

Fun fact:

My cash ratio has never been higher than €3,000 since I first entered the stock market (2018). This is currently an exception because I want to build up a cash reserve for the next generation.

Goal:

I don't have a specific, set goal when it comes to my investments. It's more of a hobby for me. I just enjoy seeing how my portfolio grows and how I can accompany exciting companies and be a small part of them as they develop. For me, it feels a bit like collecting: I enjoy discovering interesting companies, investing in them and watching them develop over the long term.

Thank you:

A big thank you goes to Goldesel Investing and Markus Koch, who have been with me since my first stock market steps. Without you, the share culture in German-speaking countries would certainly not be as strong! And of course a big thank you to Getquin - I've always dreamed of a platform like this! 0% bullshit, 100% investments.

I hope you like the revised version! The text is now more clearly structured, reads more smoothly and still retains your personal style.

Please let me know if you liked my story!

A little tip: My Bitpanda portfolio has a longer history, but I was too lazy to enter everything manually. I also didn't want to take over the history because, as I said, I wanted to start a new chapter in my investment history in November 2023. Overall, however, my crypto track is up €3000-4000.

$CSPX (-2,87 %)
$ETH (-2,56 %)
$BLK (-4,13 %)
$GS (-5,41 %)
$XDWD (-3,03 %)
$V (-3,45 %)
$MC (-3,9 %)
$MS (-5,17 %)
$QCOM (-4,52 %)
$JNJ (+0,38 %)
$ASML (-1,43 %)
$RBOT (-3,01 %)
$LOCK (-2,78 %)
$MRK (-0,9 %)
$UNP (-2,25 %)
$NKE (-6,45 %)
$QDV5 (-3,44 %)
$MA (-3,11 %)
$TGT (-2,53 %)
$PEP (+0,42 %)
$NU (-3,61 %)
$AAPL (-5,31 %)
$TSLA (-5,34 %)
$DOGE (+0,91 %)
$BTC (-0,21 %)
$BRK.B (-3,05 %)
$PEPE (+2,1 %)