If you only look at the price trend, you will see a classic high flyer. If you dig a little deeper, you will see something else: a potential possible infrastructure bottleneck that is just beginning to become economically relevant.

For me, the development of $SIVE (+50,91%) well explained by two terms:

🔴 TIP = Technology Inflection Point

A technology inflection point occurs when a technology goes from being an interesting niche solution to a potentially indispensable infrastructure.

This could currently be the case with photonics could happen. AI systems are generating ever larger data streams. At the same time, electrical connections via copper are increasingly reaching their physical limits. Energy consumption, heat and signal losses are increasing.

This is why the industry is investing heavily in optical data transmission. Light instead of electricity. Photonics is therefore increasingly developing from a specialist topic into a potential AI infrastructure bottleneck.

🟢 GDP = business inflection point

The business inflection point often comes later. It occurs when companies suddenly benefit economically from this technological change. also benefit economically.

New orders.

New customers.

New sales potential.

New valuations.

A current example is the example is the collaboration between Sivers Semiconductors and GlobalFoundries that was announced today. This is interesting for me because such partnerships can show that a technology is finding its way out of the development phase and towards industrial scaling.

This is precisely the point at which a reassessment by the market. The market then looks less at the past and more at the question: "How big could this market become if the technology catches on?"

Nevertheless, it remains important that Sivers is still one of the speculative stocks in my exposure spectrum. speculative stocks in my exposure spectrum. The company is not an established infrastructure heavyweight like Coherent. It is much earlier in the cycle. The opportunities are therefore greater.

But so are the risks.

For me, Sivers therefore remains above all a bet that the current technology inflection point will eventually become a sustainable business inflection point.

After all, returns are rarely generated when everyone is convinced. They often arise when a new infrastructure bottleneck is just becoming apparent.

Incidentally, Sivers is also my driving force in the NextLimits wikifolio with a current gain of 822%.

#dibs
#wikifolio
#scalelimits

NextLimits is at +107 %. All 20 positions are currently trading in positive territory 🟢 That makes me happy, of course. But what I find more interesting than the pure performance is the question of where it comes from.

Many of the strongest developments stem from topics that I have been observing for months as future technological bottlenecks:

- Photonics

- Advanced Materials

- Space Infrastructure

- sensor technology

- Directed Energy

Companies like Sivers Semiconductors $SIVE (+50,91%) or Everspin Technologies $MRAM (+0,85%) have performed particularly strongly. At the same time, the current development shows that the performance is not only being driven by individual outliers, but has so far been quite broadly distributed across the entire portfolio.

Interim conclusion: The underlying bottleneck theses currently appear to be confirmed. My thinking model here is DIBS (Dynamic Infrastructure Bottleneck Stack).

Nevertheless risk management as the search for opportunities. That is why I have already realized partial gains twice in Sivers Semiconductors and also made a partial sale in Everspin Technologies in order to limit the position sizes in the portfolio.

NextLimits deliberately focuses on topics where the next technological bottlenecks could arise. Not on what is already common knowledge today, but on the infrastructure, material and technology layers below. TechLimits stands for acute bottlenecks, CoreLimits for stability. All three form my ScaleLimits system.

This is still only just under two months. But so far the wikifolio is developing in exactly the direction I had in mind when I launched it.

#dibs
#wikifolio
#scalelimits

I noticed something some time ago: The deeper I look for technological bottlenecks, the more often I suddenly end up in Sweden. Not with Ericsson or Volvo, but with small and medium-sized deep-tech companies.

A few examples from my portfolio (the first four) or my watchlist:

- Sivers Semiconductors - $SIVE (+50,91%) Radio frequency and photonics components for AI and data networks

- Acconeer - $ACCON (+12,91%) energy-efficient radar sensors for industry and edge applications

- BeammWave - $BEAMMW B digital beamforming technology for future mobile networks

- Obducat - $OBDU B (+16,6%) Nanoimprint lithography for advanced semiconductor and photonic structures

- Hexatronic -
$HTRO (+7,52%) Fiber optic infrastructure for the expansion of digital networks

- Smoltek Nanotech -
$SMOL (+5,75%) Carbon nanostructures for semiconductors, electrolyzers and future packaging solutions

- Smart High Tech -
$SHT B (+30,61%) Special electronics and technical components for demanding industrial applications

What many of these companies have in common: They are not located at the end of the value chain, but often several levels below it. This is where new technologies are made possible in the first place. This is exactly where I look for bottlenecks.

Of course, such stocks are not for every investor. Many are small, less liquid and in some cases still a long way from stable profitability. Individual orders or capital measures can have a massive impact on share prices. Not every technology will prevail and not every company will make it to broad commercialization.

This is precisely why I do not treat them like standard stocks, but as targeted additions within a more broadly diversified technology portfolio. I entered SIVE just over 2 months ago and was already at a price return of 1,150 %, now a little less again and have taken two partial profits 😅.

The deeper you delve into topics such as photonics, sensor technology, wireless technologies or advanced materials, the more frequently Sweden appears.

Sometimes the country seems like a small, listed deep tech incubator in the middle of Europe.

Attention ⚠️ These are very speculative stocks with high volatility! No investment advice!

#dibs
#wikifolio
#scalelimits

Many AI investors are primarily looking at GPUs, memory or energy supply. I believe that the next big bottleneck is already slowly emerging: Photonics.

The background: modern AI systems have to move ever larger amounts of data. However, classic copper cabling is increasingly reaching its physical physical limits. Energy consumption, heat generation, signal losses and susceptibility to errors are increasing massively. This is why the industry is moving step by step towards light instead of electricity.

• Photonics simply put, means that data is no longer transmitted primarily electrically, but optically via light signals.
• Optoelectronics as a sub-sector combines electronics and lighting technology.
• CPO/Co-Packaged Optics describes the approach of placing optical components directly next to AI chips in order to massively improve speed, energy efficiency and bandwidth.

NVIDIA is now visibly driving this development forward. The company is investing billions in optical infrastructure and partners in the field of AI photonics. (For example, Lumentum and Coherent are currently benefiting from a 2 billion dollar investment each).

For me, this is therefore likely to be the next big upcoming AI bottleneck. What I find particularly interesting is that photonics does not consist of just one area. There are very different levels of risk and maturity within the stack.

Level 1: Established photonics infrastructure

This is where the more stable infrastructure players are located. Companies such as $COHR (+18,08%) (Coherent), $LITE (+12,44%) (Lumentum), $CIEN (+11,13%) (Ciena) or even $FN (+12,56%) (Fabrinet) are already benefiting from the fact that optical systems are increasingly moving into AI data centers.

This is mainly about:

• lasers
• optical components
• Fiber optic infrastructure
• transceivers
• Optical Networking

Level 2: Optical Interconnects & Data Center Connectivity

A field in which there is currently a lot of momentum. AI clusters require ever faster connections between GPUs, storage and switches. I'm thinking of companies like $AAOI (+9,38%) (Applied Optoelectronics), $ANET (+2,47%) (Arista Networks) or in some cases also $5802 (+2,41%) (Sumitomo Electric). Optical interconnects could develop into a central AI bottleneck in the next few years.

Level 3: Materials, substrates & manufacturing bases

This area usually receives much less attention, although it is here that important prerequisites for modern photonics systems are created. Photonics requires highly specialized materials, new substrates and precise manufacturing structures. I find companies such as $AXTI (+1,52%) (AXT), $SOI (-0,66%) (Soitec), $5802 (+2,41%) (Sumitomo Electric) or in some cases also $TSEM (+8,99%) (Tower Semiconductor).

Materials such as indium phosphide (InP), special wafer technologies and optical integration platforms are becoming increasingly important as data rates and integration density rise. And the more complex optical systems become, the more relevant the future bottleneck of "test & metrology" becomes, because these structures have to be controlled and measured with extreme precision (see my last post).

Level 4: Optionality & Next Generation Photonics

The risk increases significantly here. At the same time, however, the potential leverage effect also increases. Companies such as $LWLG (Lightwave Logic), $SIVE (+50,91%) (Sivers Semiconductors), $INFQ (Infleqtion) or even $LASR (nLight) are working on technologies that could make future optical systems even more efficient or powerful. For me, these are not sure winners. But they are often the early technological options for the next wave of infrastructure. Incidentally, Sivers will soon also be listed in parallel on the NASDAQ.

The exciting thing is that the AI bottleneck is shifting further and further away from pure compute and into the physical infrastructure of data movement.

Acute/Active:

HBM + Power & Cooling + Advanced Packaging + Energy/Grid

Future/Emerging:

Test & Metrology + Photonics

AI will not only need more computing power in the future. Above all, AI needs the ability to move gigantic amounts of data efficiently, quickly and stably.

A third AI bottleneck in the "future/emerging" category could already arise: Edge AI. More on this soon.

#wikifolio
#scalelimits