Mar 25: Agentic Robots, Edge AI, Quantum Computing beaming up!

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Two months in 2025 and the number of trends news with relevant Technology are beaming up.

The key aspects I touch in the title are the ones driving this newsletter and specifically the humanoid robots, progressively extending with Agentic autonomous capabilities and AI capabilities extending at the edge thru new chipsets and the acceleration of the Quantum Computing research and its potential disruption.

From this month, I add sometime a comment as Revenue Opportunity or Costs Optimization/Ops Excellence or Risk Avoidance as three highlights that can be found in some sections when I see hints in how Technology could be used to achieve those aspects.

I also add a new section for Job Evolution (due to Technology) that is going to be a reflection and regular update based on the input coming from different sources, like WEF 2025 Job Evolution Report and the way technology influences it.

As the variety of areas where Technology is relevant raises and having the aim to keep this newsletter as generally accessible, holistic and just one of my intellectual activities and not part of my work, I will try to keep the relevant arguments in a digest mode but I could miss some relevant and interesting topics. Please use the comments on Linkedin to suggest things to add or keep more an eye on so that I could be more in a focus to keep updating on. Also I have maintained so far the newsletter agnostic by suppliers and not targeting specific industries but I could have some vertical on industries, especially when I will give some recommendations if I think would apply to one specific industry or function more than others.

As reminder, I have added a part?“What could happen?“?to give future predictions and correlations for the upcoming months and a section “So what?” to comment on former guesses and how they went.

The hints I recommend represent just a minimal fraction of the possible ideas (the what) I could suggest and there are several ways to apply them (the how) based on different variables, conditions and prerequisites part of my consulting analysis and execution. Each business is different and best practices help us to define the base on which we can build up the extra unique value.

For comments, just use the referred Linkedin post.

Disclaimer

This newsletter is a combination of my own analysis and insights, informed by publicly available information and industry trends.

All my comments represent my personal opinions about Digital, Data and Technology trends in enterprises, based on the news we can all read and my correlations for further conversation and exchange always constructive and respectful.

My comments on crypto or stock market are intended as bare speculations about what I suspect could happen and why but are not intended to be recommendation for market investments and I’m not an expert in the field. I recommend to refer to specialized investor experts for your wealth management.

This newsletter It’s intended to come on a monthly/quarterly cadence based on the relevant topics I believe make sense to share and will keep a structure as much as possible technology and vendor agnostic. I could miss to identify some relevant topics that were somehow not in my radar of regular read. Feel free to suggest further arguments missed or to keep an eye on.

Why can’t comment? I just left intentionally only comments to do on Linkedin to have one single place to exchange.

Market Evolution

From the chipset competition:

• Intel is still in an unclear state if they are going to be bought or developing but few things are more clear.
• So what?: I just guessed last month here literally “US Administration to push hard for revamping the Intel production of semi-conductors in US, embedded in the Qualcomm production and reduce their dependency on TSMC,”. Now what we just saw announced here from JD Vance is making clear that “To safeguard America’s advantage, the Trump administration will ensure that the most powerful AI systems are built in the US with American designed and manufactured chips,”. What I can speculate from this, as many investors, is that Intel is on the path to be most probably bought and on the possibilities is indeed Qualcomm, as well foundry with TSMC.
• What could happen?: I think that TSMC will anyway produce 2nm semiconductors in US this year so I would expect that a part of Intel could go to TSMC, a part to Qualcomm but I would consider also AMD part of the game that would otherwise remain too much behind.
• A relevant update that came recently is about the Chinese CXMT that is already producing semiconductors at 1.6nm and planning next year to reach 1.5nm. This is going to be most probably a big competition versus TSMC and depending on the AI chipset architectures that could be built, providing progressively much more powerful capabilities to the Chinese LLM engines like Deepseek.
• What could happen?: TSMC could get impacted at stock from the progression of CXMT as this will get more tangible as real competitor and China is pushing to reduce dependency on a market that is controlled by US (TSMC has ban to export technology to China). Obviously the level of production and expertise of TSMC has been built over many years but the threat is relevant considering the acceleration that took.
• So what?: I mentioned here in early October that Qualcomm would win against ARM due to many reasons I explained in that newsletter. Here the results that happened in February, confirm that ARM gave up.
• In the competition for AI chipsets, also OpenAI is entering with own design competing in the market of Nvidia and collaborating on the implementation with TSMC and Broadcom.
• The Stargate roadmap for 2025 is already considering 100B$ planned and few AI Datacenters to be built in US by September 2025 and will run mostly OpenAI and Oracle.
• What could happen?: I expect that Oracle will beam up in the stock market and that most probably the Deepseek will allow democratization of AI as I wrote also in last month newsletter more in detail.
• Reminder on the ?AI Chipset export restriction?from the former US Administration to go live within 120 days by the release (Mid January 2025). I spoke on it in my former month newsletter. So far I saw no news on this but I expect will create some frictions that will be somehow also a reason to accelerate the alternatives like CXMT on a more free market.
• Qualcomm to make chipset for cheap phones much more performing. This will reduce the gap of cpu intensive activities, like game playing on cheap phones that until now moved a certain generation toward high end devices.
• What could happen?: High end devices will need to find new ways to justify their premium cost add or will risk to be less often selected especially from those new generations using for gaming that would be able to replace phones as performance lack for a fraction of the cost.

Looking more on the?crypto news:

• So what?: It seems that some crypto are up and down (like XRP) and I predicted strange behavior last month here. By the way my speculation on the fact that Solana would continue to raise due to the raise of meme was wrong because not considering the fact the meme market got in the shock due a reduction of interest. The reduction of interest is the confirmation of my concerns on investing in useless meme that I said here and most recently here. Also recently $TRUMP meme got a further impact on 800K people that invested simple too late. Recently also Elon changed his name for some hours on X with the name of a meme that skyrocket for some hours and then fallen again, leaving many people with just lost money. I report all this to warn against meme coins that for me remain simply like investing money in lottery tickets where only few wins including who owns the ticket generation process.

Environment, Social, Governance (ESG)

In the?Energy?world is valid to mention:

• On the nuclear fusion energy, after January China record on 1000 seconds, raised against the former 400 seconds record of 2023, in February French CEA West, achieved new record of 1320 seconds or equivalent 22 minutes. The curve of acceleration seems consistent and starting to promise interesting improvement in the long future that maybe will be not too long.

Under the aspect of?Social, after the recent US tendency to cancellation on DEI Practices:

• Some companies like Apple kept their focus and support on the DEI so far and is giving a certain stability in their organization. However showed recently some opening on the privacy aspects that were always a key reference of their brand.
• Google announced their end of ban for AI weapons. Why is this important for me? Because Google employees were in the past highly influencing the strategic decision for Google to enter or not in some businesses and this was one area that in the past they strongly voted against ( Does anyone remember the JEDI Project?) and could influence the type of resources that could leave in the future.

AI

Most relevant updates in the general AI development:

• Google last month at the AI summit in France reported that over 18 months they saw a reduction of the AI cost for around 97%. This is going to be even further accelerating from my perspective as the AI cost will be further more cost effective, especially now with the progresses done for example from Deepseek. I keep saying what I predicted last month that we will see further democratization of the usage of AI cross the world as the cost per operation will get so cheaper.
• Costs Optimization: I would highly recommend to hold big clouds long term commitment, based on LLM and other AI computations, unless granting lowering adjustment of per unit price during the agreement as I see this pricing lowering heavily in the next few years.
• Some interesting use of AI have been recently coming from the biological world. In February has been released EVO-2, a biological open-source oriented AI engine to analyze correlations between genes (also quite far between them in the DNA sequencing) and also detecting if some sequences would already be somehow existing in some other segments in correlation with specific mutations causing specific diseases. This is an usage of AI allowing to really progress in short time on detecting and possibly solving diseases that normally would take ages to be analyzed and optimized.
• Most recently the start of Deepseek approach, including LLM distillation and some of the most recent work around training AI with AI, it’s showing that it will be less and less expensive to train AI engines. In parallel, there are today already a decent number of LLM engines designed to run on lower resources machines and the development that are happening in the AI, to build up chipsets with stronger AI capabilities, it’s progressively introducing the capability to tun AI at the edge, so near where they need to be consumed, reducing latency and making also mission critical applications realistic. This is going to open a tremendous opportunity, touching all the environments like cars and other equipments that are basically distributed and moving the calculation back near where is needed and clouds remain with the focus on bigger data and process computation. Considering the updates I gave on the Market Evolution section about new chipsets also from China with more and more AI capabilities, the acceleration of this market is happening and is bringing many consequences in the accessibility of AI that will be more omnipresent and cheaper to be consumed.

In the?robotics?some interesting updates:

• There is a proliferation of human-like robots developments with short timeline to market from different vendors (from China, Europe, US). It seems that the trend is going to accelerate and the aim is to assist in home daily tasks and industrial activities accelerating the concept of Industry 5.0 (image below)

• For example the Norvay Neo X1, Meta most recent announcement, Chinese PM01 are all examples of humanoids robots with a purpose for home assistance. This trend could be relevant and has a parallel in the manufacturing with heavier robots partially already in place and now getting more integrated. Also Tesla rumors important updates for next year with their humanoid with an industrial focus.
• Recent developments in the agents are further scaling on multi-modality that is key in the capability to interact on different dimensions.
• The edge AI is getting more concrete as more powerful chipset are developed. This is definitely relevant in the industrial IoT but has many applications also in consumer market.
• What could happen?: Here my speculation is following some of former months. I see the converge of humanoids robots grow (that could be even not humanoid liking to make people less concerns), evolution in the market of agentic to make autonomous decisions and on multi-modal ways so interacting on chat, vocal, images, physical and edge AI (I just spoke earlier in this section) to be able to make AI computation at the edge and to compensate of cloud latency for high volume, realtime elaborations and missed connectivity. As all these technologies are now more and more mature, the future equipments could be really autonomous, fast deciding without pending on delay on cloud latency and also having enough physical flexibility to assist in various activities and learn as they go. The number of applications in industries, home and customers activities would be quite immense. As I analyze more in the main job market evolution section, the demands for some of repetitive activities by different industries could accelerate the adoption of these modernized equipments.

In the AI regulations:

• One aspect I like to refer is about the AI Act that is indeed an EU regulation that is highly debated, especially from those US big tech that want to develop with limited restrictions to be faster. The concern I see here is about aspects of privacy as first, quality of data and training sources, especially if we start to have LLM trained thru distilled data from other LLM, where the original source of content and its quality, get really hard to be maintained. Someone made the association with when social networks accelerated their introduction on the market and gained limited regulations and as consequences influenced poorly the privacy of people and caused several side effects. I think a way forward on AI governance will need to find a compromise way that can’t be fully open and can’t be fully blocked but need to happen now, not in 5 years.
• What could happen?: The data we have today in some trained platforms could be violating copyrights as in many recent conversations happened and could have bias based on how have been trained. Agents running on top of them could have quality problems in answering according to proper boundaries set and on the source of training.
• The energy consumption of AI is also part of the debate and will be relevant even if mitigated by the innovation coming from the most recent discoverages.
• What could happen?: Some companies could decide to self regulate to grant a proper conscious way to consume AI products and that could raise the standards and expectations toward the big tech suppliers of those technologies. In some cases we would have augmentation, where the employees uses AI to enhance themselves but would be still accountable for decision but there are many uses cases of full automation that would put autonomous AI agents in total responsibility of answers and decisions. A company would link its credibility not only to its employees but to its AI governance. Imagine a company with a fully automated AI customer service that would give impolite, wrong answers or even harmful answers to customers. The reputation of the company, not of the AI, would be quickly impacted. This is one out of 1000 examples I could quickly imagine.

Quantum Computing

Relevant changes in the Quantum Computing:

• As you maybe remember in my January Newsletter (referring to news of December 24) I spoke about the acceleration on the Quantum Computing provided by Google Willow and its modular approach. In this March Newsletter I report the update, only two months later, from Microsoft with its Majorana new quantum chipset. Interesting is that both players play a different approach on the same target to achieve the quantum computing predominance. Google approached the errors from noise of qubit interference with an error reduction approach (you can find in my former newsletter I referred before). The approach of Microsoft is different and building new materials to be able to create new states and build qubit that would not interfere between them. The aim for both big tech is to achieve the supremacy of 1million qubit. This level of supremacy would be able to crack also most of the actual algorithms not PQC (Post Quantum Cryptography) compliant and there is a progressive believe that tis happening in the next 5 years, not 20 years.
• I have found interesting a recent development in the area of distributing qubit cross wide networks. This is still at a study level but potentially I see could help to build up much more distributed quantum computing if would be able to guarantee the distribution of quantum information with low rate of error in transmission of information.
• Also Amazon come out with its quantum chipset Ocelot in competition with Microsoft and Google.
• Another interesting study still on an early simulation level but going in one direction I see relevant (AI and Quantum computing or better specifically Machine Learning and Quantum Computing) is about this work that is working on building LLM on top of quantum computing. The potential benefits are linked to the capability of problem solving and addressing at quantum level the computation.
• All the acceleration that is happening in the Quantum computing can be seen as a threat to big AI Chipset players like Nvidia and explaining why its CEO Jensen Huang was trying to push the quantum capabilities as a far solution in 20 years even if the facts are saying something different and much faster.

Job Evolution

Last month I started to look to how the World Economic Forum analyzed the future of jobs market here.

From my first analysis that you can find in the link above, there is a clear shift in jobs market in the next 5 years, with a big component of automation that is playing a key factor and a strong level of up-skilling resources and many millions of jobs created and in part displaced.

Avoiding to repeat concepts and first opinions already shared in the former newsletter, I want to take only few takeaways relevant based on the new skills required in the future and start from there to analyze few other aspects of the WEF 2025 Future Jobs Market Report.

From the Figure 3.6 is of the report is visible the main skills identified as needed in the next 5 years and some skills that went out of scope.

Reading carefully the documentation, some skills out of focus like Manual dexterity, are considered still existing for really complex manual jobs but the effort to build them is much higher than gaining for example Technological literacy and for this reason in many jobs will shift the focus of the demand. The AI will make also many of those skills marked as out of focus less relevant. You can find for example programming, as the AI is doing a certain level of it but is going to be a required skill for example the systems thinking that is normally allowing to evaluate better the quality of the output of an AI to be used. I still debate that reading and writing and mathematics for me will be relevant but most probably the view of the interviewed people is that AI will compensate the skill gaps of the people with limited knowledge but I doubt on having strong analytics skills without having developed former reading and writing skills.

I focused the exercise for this month, looking to the view of industries and how the activities get automated. Before to pass on this, let me give few definitions. An activity is defined as manual if mainly done by a person. It’s considered automated if is done completely by a machine, it’s considered augmented if is done by a person with an AI integrated somehow.

Different industries react with different percentage of automation but what is visible is that for every industry a certain number of tasks manual (the ones marked in blue as done by persons predominantly) is reducing, in some cases less, due to the fact are most probably high complex and specific, in some cases more.

For all the tasks that are not considered predominantly done by people, that represent 60 to 70% of tasks in the 2030, a big portion is predicted to be fully automated, means done by agentic without any human interaction and a part of it, the white part of each of the squares is the augmented part. So for example Pharma expect to have from half of the tasks predominantly done by people to 34 out of 100 and for the remaining 66 tasks, 55% of them would be automated (so no human work) and 44% would be done by humans with augmented AI.

Looking to this summary you can understand that some businesses reach a high level of automation and in some cases the automation is showing even more than 100% meaning that is eating activities done by the augmented people with AI.

This is telling us that people would get less busy with repetitive tasks and would focus more on the high value activities, so most probably less tasks but intense as complexity and value add.

This is also telling us that in the next 5 years, companies will have different activities and here below, a repetition from last month, I attach the key priorities.

As clear, the companies will have to focus on up-skilling resources, automating and hiring people that would help to do those activities to match emerging businesses and to enhance the competence to use new technologies.

I try in the newsletter to not make too deep analysis, for which I prefer to build dedicated articles or conversations but I aim to stimulate the reflection as an update to keep in consideration. Below few possible aspects to keep in consideration.

Revenue Opportunity: The automation of many activities in the backoffice, can accelerate the overall customer feedback process for products or services dramatically, reducing the time to market for innovation and the anticipation of customers needs

Costs Optimization/Ops Excellence: The introduction of a proper unique HRIS engine, allow to keep a proper track of all the workforce effectively, especially during a strategic up-skill process, identifying, classifying and developing core future skills. The optimization of workforce usage and allocation of resources can deliver saving in licensing and products allocation to workforce as there is a better focus to decide on what to invest as future needs.

Risk Avoidance: Setting a proper governance around which processes to automate first and following which criteria (not critical tasks, proper 4-eyes with human, proper PoC, quality of training engine, etc.) can mitigate risks of reputation that could have a high impact.

GG