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2023 m. vasario 28 d., antradienis

What European business makes of the green-subsidy race.

"Last summer European leaders began hearing a huge sucking sound. The source of the din? The Inflation Reduction Act (IRA), a 725-page law passed in August to speed up American decarbonisation. Europe's budding clean-tech industry, they feared, would be hoovered up across the Atlantic by the promise of handouts, which amount to around $400bn over ten years. To stop this happening, some EU politicians argued, the bloc would have at the very least to match the IRA's sums.

So far the noise has turned out to be mostly in the politicians' heads. Worries about a green exodus have subsided. When the continent's heads of government gathered recently in Brussels, they did not shower billions of euros more on the EU's greening efforts—which are already comparable to the IRA in their generosity. Nor did they (for now) further water down rules against state aid, which would have encouraged member states keen to splurge. Instead, they focused on making the system for doling out the cash more efficient.

In the eyes of its European fans, the beauty of the IRA is less its size than its simplicity. Rules are the same all over America. Getting tax credits, grants or soft loans will be straightforward provided a firm meets the criteria, such as investing in a targeted sector. The law sets aside sums for specific technologies, such as solar energy or carbon capture and storage (see chart). Producers of "green" hydrogen, made with renewable power, can get tax credits of up to $3 per kilogram of the gas.

Replicating this set-up exactly would be unthinkable in Europe. The EU may see itself as an ever-closer union, but taxes are still a national affair, which rules out continent-wide tax incentives. If member states want to offer their own credits, or other subsidies, they typically need the approval of the European Commission, whose job it is to ensure a level playing-field in the EU's single market. To the resulting cacophony of national schemes, the EU has recently added a few bloc-wide grant programmes, such as InvestEU and Innovation Fund, to support clean tech.

The result is jarring, particularly for smaller companies in need of funds to scale up their projects, says Craig Douglas of World Fund, a venture-capital firm, who has long experience in dealing with the EU's subsidy bureaucracy. To have a chance at tapping one of the many pots, startups often have to hire pricey consultancies to help them write grant proposals. "We would need at least four people full-time to figure this out," explains Vaitea Cowan, co-founder of Enapter, a maker of electrolysers, machines that produce hydrogen.

Once an application is filed, it can take months, or years, before a decision is made. In the case of Plastic Energy, which recycles plastic waste, it once took so long that "we had to file again because the delay made us miss a deadline", reports Carlos Monreal, its boss. Decisions tend to come without explanation. "It's a black box. There should be a dialogue," says Henrik Henriksson, CEO of H2 Green Steel, which is erecting a steel mill in northern Sweden powered by green hydrogen. And the EU's green subsidies are often poorly targeted. Jules Besnainou of Cleantech for Europe, an industry body, notes that most of the money goes not to the continent's startups, which tend to be more innovative, but to big established firms, which do not always need government support.

The commission's draft "Green Deal Industrial Plan", unveiled on February 1st, tries to deal with these shortcomings. The plan is meant to simplify the EU programmes and streamline the approval of national green-finance tools in Brussels. It proposes an "administratively light" auction for green-hydrogen producers: winners will receive a premium, based on their bids, for each kilogram of the gas produced over ten years. The scheme will offer incentives to the tune of €800m ($860m). The IRA has clearly shocked the EU into thinking harder about its green subsidies, says Jeromin Zettelmeyer, who heads Bruegel, a think-tank in Brussels.

That may be so. Still, those who have read the eight pages dedicated to "speeding up access to finance", which mention no fewer than a dozen different acronym-rich programmes, may be excused for not holding their breath. Claudio Spadacini, CEO of Energy Dome, an Italian firm which uses liquid carbon-dioxide to store energy, approves of the EU's moves but still hopes to take advantage of the IRA. Ms Cowan of Enapter, whose firm has just built a factory in Germany, is getting lots of calls from American state governments since the IRA was passed. "They are rolling out the red carpet," she says. Whoosh.” [1]


·  ·  ·1.  "What European business makes of the green-subsidy race." The Economist, 14 Feb. 2023, p. NA.

Palangoje atidarytas paminklas fašistiniam Lietuvos diktatoriui Smetonai

 Dalyvavo ponas Nausėda. Tai parodo, kokia yra dabartinė Lietuvos valdžia. Gėda, Nausėda, tikrai gėda.

Atėjo metas keisti kovos su pinigų plovimu strategiją

"Su pinigų plovimo kovojančių Jungtinių Tautų duomenimis, pasaulyje per metus vidutiniškai „išplaunama“ nuo 0,715 iki 1,87 trln. Eur, o tai sudaro apie 2–5% pasaulinio bendrojo vidaus produkto (BVP). Visgi, tik mažiau nei 1% šių lėšų valdžios institucijos sugeba konfiskuoti. Pabandykime panagrinėti šios srities Lietuvos statistiką. Lietuvos BVP 2022 m. sudarė kiek daugiau nei 60 mlrd. Eur. Taigi, labai grubiu vertinimu, 2–5% nuo šios sumos sudarytų 1,2–3 mlrd. Eur.

Bet galime skaičiuoti ir kitaip. Vien Lietuvoje licencijuotos „fintech“ įmonės (elektroninių pinigų institucijos ir mokėjimų įstaigos) 2021 m. atliko 194 mlrd. Eur vertės operacijų. Taigi, darant itin konservatyvią prielaidą, kad 1% visų operacijų gali būti susijusios su įtartina, „nešvaria“ veikla, vis tiek gauname tikrai įspūdingą didesnę nei 1 mlrd. Eur sumą. Ir į šią statistiką dar net neįskaičiuotos didžiųjų bankų ar kriptokeityklų atliekamos mokėjimų operacijos.

 

Norint apsaugoti finansų sistemą nuo įtartinų pinigų, finansų įstaigos ir kiti įpareigoti subjektai turi tokius atvejus identifikuoti bei informuoti Finansinių nusikaltimų tyrimo tarnybą (FNTT). Tokių pranešimų skaičius kas metus auga ir, jeigu 2017 m. FNTT gavo 883 įtartinos veiklos pranešimus (vadinamuosius STR), tai 2021 m. STR jau buvo pateikta 45.709.

Suprantama, FNTT tokio didelio skaičiaus STR išsamiai analizuoti negali, todėl atrinkti ir išsamiau buvo analizuoti tik rizikingiausi – 610 STR, o Lietuvos teisėsaugos institucijoms buvo išsiųsti 229 išanalizuoti STR. Tik 15 atvejų buvo pradėti ikiteisminiai tyrimai pagal Baudžiamojo kodekso 216 str. „Nusikalstamu būdu gauto turto legalizavimas“.

Lietuvoje 2021 m. sustabdytų piniginių operacijų suma buvo 65 mln. Eur, tačiau tik 11 mln. Eur vėliau buvo pritaikytas laikinas nuosavybės teisių apribojimas pagal baudžiamojo proceso kodeksą. Ir tai dar ne faktas, kad tie 11 mln. Eur, ištyrus nusikalstamas veikas, buvo vėliau  konfiskuoti. Taigi, panašu, kad oficialioji statistika Lietuvoje toli gražu neparodo tikrųjų pinigų plovimo mastų.

Pavyzdys su plėšimais

Įvairių šalių pasaulio policijos pajėgos dar praėjusiame amžiuje suprato, kad vien tiriant nusikaltimus pažangos nepadarysi. Todėl nusikaltimų prevencijoje atsirado naujos tendencijos, kurios įprastinę reaktyvią (nukreiptą į nusikaltimo ištyrimą) policijos veiklą, pakeitė į proaktyvią veiklą (nukreiptą į nusikalstamumo priežasčių šalinimą).

Juk visuotinai žinoma, kad nusikaltimui įvykti būtini 3 elementai: nusikaltėlis, vieta ir auka. Eliminavus bent vieną iš šių elementų, realu užkirsti kelią nusikaltimui įvykti. Eliminuoti nusikaltėlį ar auką yra pakankamai sudėtinga, tačiau surinkti daugiau apibūdinančios informacijos apie nusikaltimo vietą yra nemažai instrumentų.

Paimkime konkretų pavyzdį –  privataus turto vagystes Vilniuje. Preziumuokime, kad surinkome statistiką apie tipinius tokio tipo nusikaltimus sostinėje:

Taigi, logiškos rekomendacijos norint išvengti tokio tipo nusikaltimų būtų įrengti vaizdo stebėjimo, automobilių numerių automatines nustatymo sistemas šiose gatvėse, įpareigojant policijos patrulius tarp 01.00–05.00 val. dažniau aplankyti šiuos maršrutus bei tikrinti ir fiksuoti automobilius ir asmenis atitinkančius įtartinumo kriterijus. Papildomai galima gerinti tų vietų apšvietimą, organizuoti bendradarbiavimą su vietinėmis gyventojų bendruomenėmis.

Pradėti nuo šaltinių išgryninimo

Lygiai taip pat reikėtų keisti ir kovos su nusikalstamumu bei pinigų plovimo prevencija strategiją.

„Sek paskui pinigus“ principas, gal ir veikęs praėjusiame amžiuje, yra reaktyvus ir dabartiniais laikais jo efektyvumas yra žemas.

Taigi, finansų institucijoms reikėtų pradėti proaktyvią prevencinę veiklą. Nuo ko pradėti? Iš pradžių reikėtų suprasti ir žinoti didžiausias pajamas organizuotam nusikalstamumui duodančiu pirminius nusikaltimus. Interpolo ekspertai 2022 m. labiausiai populiarėjančiais įvardijo:

Papildomai dar galima pridėti:

Šių nusikaltimų vykdymas organizuotam nusikalstamumui duoda labai didelį pelną ir kelia sąlyginai mažą grėsmę, kad nusikaltėlis bus nustatytas arba bus skirta reali laisvės atėmimo bausmė. Taigi, vertėtų daugiau dėmesio skirti pirminio nusikaltimo ir vėliau naudojamo pinigų plovimo modelio suvokimui ir jo priežasčių šalinimui.

Riziką keliantys požymiai

Viso pasaulio pinigų plovimo prevencijos specialistai pripažįsta, kad po sukčiavimo vėliau pinigų įsisavinimui dažniausiai naudojamas prekyba grįstas pinigų išplovimo metodas. Šiam metodui vykti dažniausiai naudojamos fiktyvios įmonės. Taigi, prevenciškai, o ne tik reaktyviai, siekiantys veikti priežiūros institucijų atstovai ir finansų institucijų pinigų plovimo prevencijos specialistai dėmesį turėtų atkreipti į šiuos padidintą pinigų plovimą riziką keliančius veiksnius:

Nustačius du ar daugiau rizikos faktorių, vertėtų apie klientą surinkti kuo daugiau papildomų duomenų. Renkant informaciją apie juridinį asmenį derėtų nesikliauti vien kliento pateikiama informacija ar dokumentais, o aktyviai naudotis viešųjų šaltinių žvalgybos (angl. Open-source intelligence, OSINT) ir kitais viešai prieinamais informacijos šaltiniais, tokiais, kaip lėktuvų, laivų judėjimo stebėjimo įrankiais, palydoviniais žemėlapiais ir pan.

Žinoma, didinant informacinių technologijų sprendimų naudojimą finansinių sukčiavimų prevencijoje, reikia nepamiršti paraleliai investuoti ir į pinigų plovimo prevencijos specialistų kompetencijų didinimą, nes būtent jų sprendimai dažniausiai nulemia prevencinių veiksmų efektyvumą.

Komentaro autorius – Mindaugas Petrauskas, AMLYZE finansinių nusikaltimų prevencijos vadovas"



Artificial intelligence can become Lithuania's competitive engine, but we have to revolutionize the scientific system

"Achievements in the field of science always allow at least a small part to touch the future. When forming possible scenarios for the future of the state, the analysis of the evolution of science can become one of the most important catalysts for the country's breakthrough. Today, the eyes of the whole world are focused on artificial intelligence (AI) innovations and their impact on the future economy and social life. According to AI expert Dovydas Čeilutkas, this is a field of science that we must pursue now.

 

D. Čeilutka is the president of the Lithuanian Artificial Intelligence Association, a data scientist at Vinted UAB, head of the data science program at Turing College UAB, a member of the State Progress Council, contributing to the preparation of Lithuania's future vision "Lithuania 2050".

 

How are the issues of science, AI development and impact on the state reflected in the current vision of the future of Lithuania? Are they getting enough attention?

 

In making clearer steps for the future of the state, we should pay much more attention to science. Science is a necessary condition for the successful existence of AI, and AI is extremely closely related to business breakthroughs, it is a particularly important technology for the economy of the future. 

 

Unfortunately, we still lack the understanding that we will not achieve the growth of AI and other advanced technologies if we do not have an orderly system of education and higher education. We have a lot of catching up to do.

 

AI is one of the fastest growing fields of science. Things that were important three years ago are completely obsolete today. Both the state and business must be able to quickly absorb AI innovations. However, we are still not able to quickly adopt the innovations carried out in the leading countries, we lack a central engine. This is holding back and will further hold back AI projects in the future.

 

Lithuanian science lags behind in the field of the latest technologies, achievements related to innovation are poor. Most achievements in the field of artificial intelligence come from Lithuanians who are self-taught or have graduated from foreign universities. This does not mean that Lithuanians will never achieve anything in this field, but most likely they will have be returning from abroad or creating while there. This is one of the biggest weaknesses in achieving the desired future scenario of the state. On the way to it, science should get a central role.

 

What are the most important drivers of AI innovation today, do businesses and government policy makers manage to catch up and understand them?

 

When a new technology is developed, it often involves people who have no formal training in the field, e.g. now there are many physicists, econometricians, mathematicians and even philosophers working in the field of artificial intelligence. It is important that innovation pioneers who understand the value of new technology pass on their knowledge and are able to prove that the new technology can successfully solve problems that have not yet been explained. However, the activity of technology self-taught people is not a systemic solution, and systemic solutions are extremely important when forming the state strategy.

 

While self-taught people are successfully delving into the benefits of innovation, familiarizing businesses with the latest technologies is difficult. Big world companies like Apple or Google solve this by hiring the smartest and most accomplished people in this research field, working in world-class AI development laboratories. Research-oriented companies, such as Open AI or Deep Mind, work extremely closely with academia and contribute to scientific research activities themselves. AI talents are interested in working in such companies, because the person doing the research can solve new problems relevant to the business. Both sides win.

 

Do we have anything to offer world-class AI talents in Lithuania? How can we attract them?

 

We face several obstacles when it comes to attracting talent. The first is that we are small, it is difficult to compete with, for example, Holland or Switzerland, which have larger international cities.

 

The level of wages in Lithuania makes it extremely difficult to compete with the wages offered in US or Western European companies.

 

Arriving talents often want to work with the academy, especially Lithuanians returning after studying or working abroad. Unfortunately, cooperation with the Lithuanian scientific field is rarely successful. Lithuanian science is quite closed - this is a big problem.

 

Some people are also discouraged by the geopolitical situation. When the events between Ukraine and Russia started, we organized an international conference, we invited many famous international scientists, but people were afraid to come, some chose to participate remotely. We have a huge border with Belarus, which is equivalent to Russia in the eyes of Westerners.

 

However, bigger Lithuanian start-ups (English scale-up) are starting to work with problems of the same scale as the big global technology companies. We have data, an interesting problem, incoming talent can find a new phenomenon, and we can solve a specific problem. So we start to have traction points, good data infrastructure, new working technologies, tools needed  to analyze these problems.

 

The disadvantages I have listed, which make it difficult to attract science and innovation talent, are not insurmountable, but an incentive is needed to help attract this talent. Creating these incentives can successfully counterbalance existing weaknesses.

 

You mentioned that the cooperation of incoming talents with the academy does not bring the desired results. In your opinion, what is the reason for the closed nature of Lithuanian science?

 

I think there are dozens of reasons, but if one of them is solved, the scientific situation in Lithuania would improve significantly. These are economic circumstances and the distribution of funding. Funding of science in Lithuania is incredibly poor. Our professors earn less than second-year students - this is information that reaches me from people working in the academy and official statistics.

 

Friends, scientists, share examples of job advertisements that indicate a salary of 300 EUR. These numbers throw you off track, you feel like you're living in a parallel world. Private institutions can offer ten times the reward for a scientist's knowledge. So far, all the people I've met who work in the academy do it purely out of personal motivation, without thinking about money.

 

It is strange that there is no real funding for science, but a lot is invested in the restructuring and construction of buildings. It seems that academic institutions are primarily managers of real estate rather than problem-solving engines for the improvement of science.

 

The growth of science is partially hindered by restrictive laws and evaluations. Our scientists are not evaluated for their participation in international conferences, although in the field of AI it is the most important indicator of a scientist's performance. While scientific journals are extremely important in many other fields, they are less relevant in AI. The speed of the AI world is extremely fast, conferences are more suited to the pace of this field.

 

Can we keep up at this rate? How does Lithuania currently look on the global AI map?

 

We look really sad on the global AI map. In Lithuania, PhD students or researchers working with AI do not have presentations at the world's largest conferences, such as NeurIPS, ICML, CVPR, which are like the AI Olympiad or the Oscars. It is the epicenter where all new ideas and concepts are presented and discussed.

 

It's sad, but Lithuania is cut off, the AI world knows nothing about us. There are many good people working in the field of Lithuanian science, but they are scattered, there is no ecosystem that helps to grow, create change, no systemic effect is created, and individual scientists are unable to change the course of scientific development.

 

We see success stories abroad, where talented AI researchers from Lithuania work, we keep in touch with them: Gintarė Karolina Džiugaitė, Justas Dauparas, to whom we presented an award for merit last year, and dozens of others.

 

There are solutions, but they must not be evolutionary, but revolutionary, radical, otherwise we will hardly be able to change anything. We are not the only ones who want to be better, competition in this area is growing between all countries, every country understands that AI is a particularly important technology that will become the engine of the economy for the next century.

 

What is the role of AI in the development ecosystem of businesses, especially startups? Are Lithuanian startups moving in the right direction?

 

We see a lot of good changes in the ecosystem of Lithuanian startups, especially in the laws and tax base. A decade ago, creating a startup in Lithuania was extremely difficult. There were no employee options, and their taxation was extremely unfavorable. Most chose to create startups in Britain or the United States. However, there is a change, progress has taken place, this encourages people to choose a more favorable legal base and create a new startup in Lithuania.

 

We have two types of startups in Lithuania. Due to their size, the previously mentioned scale-ups take on interesting problems and are able to solve them with the help of international talents.

 

Many smaller startups base their operations on AI technologies early in their development. Many of our association members are small startups whose main product is AI solutions. Thus, even a team of just a few people can work on interesting problems - AI allows solving new global problems for Europe and the world, rarely limited to Lithuania. 

 

 For example, Pixevia's autonomous store concept developed in Lithuania can be successfully applied in any country in the world.

 

An autonomous store is an example of the use of AI in everyday life. Do we need to awaken the curiosity of the general public - how can we use AI more widely in life, or is it knowledge that bites everyone?

 

The saying of Andrew Ng, an AI expert and scientist who has done a lot for the world, that AI is the new electricity, has already become famous. Not many people understand exactly how electricity works. Most likely, only at school did we get acquainted with the basics of operation, understand the safety requirements. This will be the understanding of AI in the future. Already, it would be hard to find a product, especially from big tech companies, that doesn't have AI components. Tens or hundreds of these components are commonly used. For example, many of us who in the video chat used in the service, we would count at least ten components of AI technology (models for object segmentation, audio-to-text translation, etc.), and the team that created it would reveal several dozen more. But we as users do not need to understand how the model of the artificial environment in our conversation works, how it is updated or improved - we have the result and use it for our daily needs.

 

In the future, there will be even more user-friendly AI models, and we will learn to understand them in the same way we learned to use electrical appliances. The new and currently very relevant ChatGPT is already known and used by many people. Apparently the first product based entirely on the use of AI, the general assistant is useful for many people who are not AI experts. More and more such products will appear, they will be more specialized.

 

Applying AI in everyday life will be easy and simple if we have a good education about the main aspects of this innovation, the consumer side of AI. In Lithuania, a few people are engaged in AI education, but in the future, if a few hours are devoted to familiarization with the basic principles of AI, this knowledge will be sufficient for everyday human needs, using AI products.

 

What do you see as the global threats to the development of AI? What arrangements do we need to make so that AI developers and key managers choose a utopian rather than a dystopian direction for AI growth?

 

Education will help people understand that there is no need to fear and hope for the worst case scenario. The aforementioned Andrew Ng says that thinking about a dystopian AI future is like thinking about overpopulation on Mars. My attitude is the same. It is true that most surveys of AI experts show that in the 2050s we will create a general AI (artificial general intelligence) - a single AI model smarter than a human. Almost all future scenarios in this context are dystopian, looking at how superAI will take over the world. But these potential threats are already being addressed by a great many smart people.

 

It is worth getting acquainted with the research of Nick Bostrom, Eliezer Yudkowski and their colleagues. We need to think of AI like nuclear energy - it's a very useful thing, but we can't build nuclear power plants and then tackle security. We need to analyze the risks beforehand in order to make the AI models safe. It's hard to do, but we have the time, the advanced research teams, and the talent to address these issues right now.

 

While scientists are taking care of our security in the future world of AI, what kind of agreements should we as a society and the state look for in Lithuania right now, aiming for a positive "Northern Star" scenario rather than a dystopian one?

 

Looking at the "North Star" scenario, I think we don't have a mechanism, a model, to help achieve the goals of this direction. Data science, statistics, machine science always rely on models that reveal causal relationships and help to plan further steps. We said that we want to live well, the state must be resilient, the nation motivated, economic well-being achieved, social security, beautiful nature nurtured, and there is no shortage of funds in the regions. These are nice goals, but we seem to have no conceptual mechanisms for how we want to achieve them. We don't have a plan.

 

I think, moving towards the desired scenario, we must first develop the economic growth of the country. As the economy improves, we will get closer to our goals. The role of AI in achieving economic growth will be crucial. Heads of state and CEOs of major companies around the world already understand the importance of AI for the world of the future, even though we are currently witnessing the beginning of the technology's development.

 

Just like the huge changes that electricity once brought, the changes of the "new electricity" - AI - will be very significant in the life of our country. The ability to create technologies and products based on AI can be the main engine that will allow Lithuania to catch up and overtake many other countries. However, we need to organize science, cooperation between science and business, and the promotion of the startup ecosystem. These are the main elements we should focus on. You don't have to be distracted by a hundred different things. By pursuing the above-mentioned goals, we will eventually get closer to the elements of a good life that are extensively listed in the "North Star" script.

 

The State Progress Strategy "Lithuania 2050" is prepared using the innovative method of future insights. The duration of its implementation is more than twenty years (from 2024 to 2050). It is planned to present the project to the Seimas in the spring of 2023.  The State Progress Strategy "Lithuania 2050" is prepared by the Government Chancellery in cooperation with the Center for Strategic Analysis of the Government (STRATA), the Future Committee of the Seimas and Vilnius University. It is implemented as part of the project "Establishment of an Evidence-Based Management Competence Center, No. 10.1.1-ESFA-V-912-01-0025", which is financed by the European Social Fund. More information at www.Lietuva2050.lt."