Category Archives: Open Source

Artificial Intelligence in Combating Climate Change

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Artificial Intelligence (AI) is becoming a key tool in the fight against climate change. According to The Guardian, “AI helps model climate changes and develop adaptation strategies.” This allows scientists and policymakers to make more informed decisions to mitigate the effects of global warming.

However, as noted by BBC News, “using AI in climate research requires significant computational resources, which can increase its carbon footprint.” It’s essential to balance the advantages of AI with its environmental impact.


Resources:

  1. The Guardian – AI in Climate Change Mitigation
  2. BBC News – Environmental Impact of AI in Climate Research
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CRYTOGEDON

Reading Time: 5 minutes

INTRODUCTION

Crypto assets are no longer on the fringe of the financial system.

The market value of these novel assets rose to nearly $3 trillion in November from $620 billion in 2017, on soaring popularity among retail and institutional investors alike, despite high volatility. This week, the combined market capitalisation had retreated to about $2 trillion, representing an almost four-fold increase since 2017.

Amid greater adoption, the correlation of crypto assets with traditional holdings like stocks has increased significantly, which limits their perceived risk diversification benefits and raises the risk of contagion across financial markets.

The stronger association between crypto and equities is also apparent in emerging market economies, several of which have led the way in crypto-asset adoption between returns on the MSCI emerging markets index and Bitcoin was 0.34 in 2020–21, a 17-fold increase from the preceding years.

Stronger correlations suggest that Bitcoin has been acting as a risky asset. Its correlation with stocks has turned higher than that between stocks and other assets such as gold, investment grade bonds, and major currencies, pointing to limited risk diversification benefits in contrast to what was initially perceived.

Crypto assets have experienced tremendous growth over the past two decades, with the number of coins increasing from just Bitcoin in 2009 to over 5,000 currently, and reaching a total market capitalization of over USD 3 trillion towards the end of 2021. However, this growth has been accompanied by significant volatility, with most crypto coins going through several cycles of rapid growth followed by dramatic collapses. This is reminiscent of other periods in financial history in which private forms of money have proliferated in the absence of adequate government regulation, leading to frequent financial crises (such as in the US during the “Free Banking Era” of 1837–1863).

The rapid ascent of crypto assets, coupled with their increasing mainstream adoption, has generated concerns among policymakers and regulators, who are mindful about the potential contagion risks to other financial markets as well as the broader macro-financial. Crypto asset markets can both act as a source of shocks or as amplifiers of overall market volatility, thereby having the potential to have significant implications for financial stability. Consequently, policymakers face an imperative to enhance their comprehension of the interconnections between crypto assets and financial markets, enabling them to devise regulatory frameworks that effectively counteract the potential adverse consequences of crypto assets on financial stability.

The complex and rapidly evolving nature of the crypto market pose challenges for regulators in effectively assessing and addressing associated risks. Crypto assets encompass a wide range of technological attributes and features, serving means of payment, to store of value, speculative asset, support for smart contracts, fundraising, asset transfer, decentralized finance, privacy, digital identity, governance, among others. However, their relationship with traditional financial assets, particularly in terms of diversification potential, remains a subject of debate. While substantial research has investigated the nature, direction and intensity of linkages between crypto assets and crypto assets and other financial assets, the findings are still relatively inconclusive and paint a complex picture of interdependencies.

The multifaceted interaction channels between crypto assets and financial markets may make it challenging to assess the relationship, while it may also have changed over time.

On the one hand, a “fight-to-safety channel” would suggest that investors may allocate their funds into crypto assets during periods of economic uncertainty or market stress if cryptos are perceived as safer and offering a good hedge to certain financial assets. Crypto assets can thus provide diversification benefits if their correlation with certain classes of traditional assets is low. However, their tendency for high volatility raises important concerns. Another potential channel is the “speculative demand channel”, which would suggest that demand for crypto assets may increase during times of high financial market risk appetite, as cryptos offer the potential for high returns due to their volatility. Further channels could be related to market liquidity and to information spillovers or investor sentiment, which can lead to additional comovement between various classes of financial assets and crypto markets.

This dataset consists of the daily closing price of the five largest crypto assets by market capitalization namely Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), Binance (BNB), and Tether (USDT) as of December 31st, 2021. The stock market is captured by the US S&P500 index, and we also include the Brent oil price, as well as the 10-year U.S. treasury bill as control variables to account for the possible impact of variations in commodity prices and financial condition on asset prices. The US S&P500 tracks the performance of 500 large companies in leading industries and represents a broad cross-section of the U.S. economy and is widely considered representative of the overall stock market . Tether (USDT) is a stable coin used in this study to provide insight into the inflow and outflow of funds in the market and as a tool for hedging against the volatility of the crypto market. For this reason, the USDT is likely to be more sensitive to the movement of price in the crypto market. presents a time series plot of the sampled variables. The daily datasets are in U.S. dollar currency and span from the period January 2018 to December 2021, excluding non-trading days for uniformity. Data on cryptocurrencies (Bitcoin, Ethereum, Ripple, Binance, and Tether) were retrieved from Yahoo Finance, whereas data on Brent oil, and U.S. 10-year treasury bills were retrieved from the U.S. Federal Reserve Bank of St. Louis. Additionally, the U.S. S&P500 was retrieved from Investing market indices. The baseline specification of this study considers the S&P500 index as an endogenous variable whereas cryptocurrencies and the control variables are used as dependent variables.

The increased and sizeable co-movement and spillovers between crypto and equity markets indicate a growing interconnectedness between the two asset classes that permits the transmission of shocks that can destabilise financial markets.

CONCLUSION

This analysis suggests that crypto assets are no longer on the fringe of the financial system, IMF said.

The market value of these novel assets rose to nearly $3 trillion in November from $620 billion in 2017, on soaring popularity among retail and institutional investors alike, despite high volatility. This week, the combined market capitalization had retreated to about $2 trillion, still representing an almost four-fold increase since 2017.

Amid greater adoption, the correlation of crypto assets with traditional holdings like stocks has increased significantly, which limits their perceived risk diversification benefits and raises the risk of contagion across financial markets, according to new IMF research.

By- Shannul Mawlong 50401

AI Sources: chat gpt 4

Other sources: https://www.business-standard.com/article/markets/crypto-prices-moving-in-sync-with-stocks-posing-systemic-risks-122011200477_1.html

https://www.sciencedirect.com/science/article/pii/S2405844023033868https://www.elibrary.imf.org/viewhttps://www.imf.org/en/Blogs/Articles/2022/01/11/crypto-prices-move-more-in-sync-with-stocks-posing-new-risksjournals/001/2023/213/article-A001-en.xml

Cryptocurrency’s Dark Side: Money Laundering and Other Criminal Activities

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Cryptocurrency’s Dark Side:

Cryptocurrency has become increasingly popular in recent years, but its anonymous nature and ease of use have also made it a prime target for criminals. Money laundering, drug trafficking, and terrorist financing are just a few of the illicit activities that cryptocurrency has been used to facilitate.

One of the biggest challenges in combating cryptocurrency-related crime is the difficulty of tracing transactions. Unlike traditional financial transactions, cryptocurrency transactions are not subject to the same regulatory oversight. This makes it difficult for law enforcement to track down criminals and recover stolen funds. Another challenge is the international nature of cryptocurrency transactions. Criminals can easily transfer cryptocurrency across borders, making it difficult for law enforcement to jurisdictionally investigate and prosecute crimes.

Despite these challenges, there are a number of steps that can be taken to address the use of cryptocurrency for criminal purposes. One important step is to increase regulation of the cryptocurrency industry. This would help to increase transparency and make it more difficult for criminals to use cryptocurrency anonymously. Another important step is to improve international cooperation in investigating and prosecuting cryptocurrency-related crimes. Law enforcement agencies need to be able to share information and coordinate their efforts across borders in order to effectively combat this type of crime.

Market Manipulation

Cryptocurrency markets are highly susceptible to manipulation. This is due in part to the lack of regulation and the relatively small size of the cryptocurrency market.

One common form of market manipulation is wash trading. Wash trading is when an insider buys and sells the same cryptocurrency at the same time in order to create artificial trading volume. This can make the cryptocurrency appear more popular and valuable than it actually is.

Another common form of market manipulation is front-running. Front-running is when an insider uses their knowledge of upcoming trades to place their own trades ahead of time. This allows them to profit from the price movements that they have created.

Market manipulation can have a significant impact on investors. When investors are misled into believing that a cryptocurrency is more valuable than it actually is, they may be more likely to invest in it. This can lead to significant losses when the price of the cryptocurrency eventually falls.

There are a number of steps that can be taken to address market manipulation in the cryptocurrency market. One important step is to increase regulation. Regulation would help to increase transparency and make it more difficult for insiders to manipulate the market.

Another important step is to educate investors about the risks of market manipulation. Investors need to be aware of the different ways in which the market can be manipulated and how to protect themselves from becoming victims.

Investment Risks

Cryptocurrency is a very risky investment. Cryptocurrencies are volatile and unregulated, which means that their prices can fluctuate wildly. This makes them a poor choice for investors who are not comfortable with a high degree of risk.

In addition, cryptocurrency exchanges have been hacked on numerous occasions, resulting in the theft of millions of dollars worth of cryptocurrency. Investors also face the risk of losing their cryptocurrency if they forget their private keys or if their wallets are compromised.

Another risk associated with cryptocurrency investment is the potential for fraud. There have been a number of cases of cryptocurrency scams and Ponzi schemes. Investors need to be careful and do their research before investing in any cryptocurrency.

Environmental Impact

Cryptocurrency mining is a very energy-intensive process. In 2021, the Bitcoin network consumed more electricity than the entire country of Argentina. This is a major environmental concern, as it contributes to climate change.

In addition, cryptocurrency mining often takes place in countries with cheap electricity and lax environmental regulations. This can lead to environmental damage, such as air pollution and water contamination.

There are a number of ways to reduce the environmental impact of cryptocurrency mining. One way is to use renewable energy sources to power mining operations. Another way is to develop more efficient mining hardware.

Regulatory Challenges

Cryptocurrency is still a relatively new asset class, and there is no clear regulatory framework in place. This makes it difficult for investors to protect themselves from fraud and other abuses.

In addition, the lack of regulation makes it difficult for law enforcement to track down and prosecute criminals who use cryptocurrency.

There are a number of regulatory challenges that need to be addressed in order to create a more stable and secure cryptocurrency market. One challenge is to develop clear regulations that protect investors and prevent fraud. Another challenge is to develop international regulations that coordinate the oversight of cryptocurrency markets across borders.

Conclusion

Cryptocurrency has the potential to revolutionize the financial system, but it is important to be aware of the dark side of cryptocurrency before investing. Investors should carefully consider their risk tolerance and investment goals before making any decisions.

https://crypto.news/various-crypto-scams-cost-users-over-32m-in-october/

https://www.electronicpaymentsinternational.com/news/signal-cryptos-dark-side-is-back-in-the-news-how-bad-is-it-really/?cf-view

https://www.coindesk.com/consensus-magazine/2023/10/20/unraveling-the-dark-side-of-crypto/

https://cryptopotato.com/dark-side-of-crypto-etf-approval-unveiling-the-hidden-risks-and-challenges-for-markets-and-investors/

https://www.financemagnates.com/cryptocurrency/education-centre/the-dark-side-of-the-blockchain/

Engine Used: DeepAI

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R(US-K)RAINE- DOOMSDAY OR MAYDAY FOR THE ECONOMY?

Reading Time: 4 minutes

Introduction:

The global economy’s gradual recovery from both the pandemic and Russia’s invasion of Ukraine remains on track. China’s reopened economy is rebounding strongly. Supply chain disruptions are unwinding, while dislocations to energy and food markets caused by the war are receding. Simultaneously, the massive and synchronized tightening of monetary policy by most central banks should start to bear fruit, with inflation moving back towards targets.

The global markets experienced immediate and significant impacts due to the Russia-Ukraine war. The surge in energy prices, triggered by the commencement of the conflict, directly affected both consumers and industries with energy-intensive operations. This impact was particularly pronounced for nations heavily reliant on energy imports from Russia. Furthermore, the escalation in energy prices exacerbated an already challenging inflation situation, partly stemming from the expansive fiscal and monetary measures implemented during the peak of the COVID-19 crisis.

Although markets have exhibited some recovery since the invasion of Ukraine on Feb. 24, 2022, considerable uncertainties persist. Looking ahead, we anticipate that inflation, economic growth, and the efficacy of monetary policy will play pivotal roles in shaping market dynamics. However, various fundamental factors will also come into play. A thorough understanding of the performance over the past year can equip investors with valuable insights to analyze potential risks and opportunities in 2023.

Equity markets displayed considerable volatility and delivered some unexpected outcomes in the aftermath of the Russian invasion, marking a turbulent year for global financial markets. The conflict triggered notable economic and investment consequences, including the departure of major multinational corporations from Russia and the removal of Russian companies from the MSCI Emerging Markets Index.

Contrary to initial concerns, European equity markets performed better than anticipated, concluding the one-year period with a 2% increase when measured in local currency. However, the strengthening of the U.S. dollar against major European currencies tempered the MSCI Europe Index’s USD returns to 3% for international investors. Despite this, there was considerable variability in returns among European countries. Nations with geographical proximity to the conflict zone and gas dependency on Russia, such as Hungary, Poland, and Germany, experienced significant negative returns. In contrast, the U.K. demonstrated resilience, finishing the year strongly despite grappling with challenges posed by energy-price inflation.

Concerns about the risk of an uncontrolled wage-price spiral do not seem justified at this juncture. Nominal wage gains are trailing behind price increases, indicating a decline in real wages. This is occurring despite robust labor demand, marked by numerous job vacancies, and a lingering labor supply shortage as some workers are yet to fully return to the workforce post-pandemic. While one might expect real wages to rise, the current scenario suggests otherwise. Paradoxically, corporate margins have expanded, driven by significantly higher prices but only modestly increased wages.

On a different note, the side effects of the sharp monetary policy tightening over the past year are starting to manifest in the financial sector, as previously cautioned. The prolonged period of subdued inflation and low interest rates had bred complacency in the financial sector regarding maturity and liquidity mismatches. The rapid tightening of monetary policy in the past year resulted in considerable losses on long-term fixed-income assets and elevated funding costs.

In a hypothetical scenario where banks, responding to rising funding costs, prudently reduce lending, there could be an additional 0.3 percent reduction in output this year. However, the financial system may face more significant tests, with nervous investors targeting institutions with excess leverage, credit risk, interest rate exposure, dependence on short-term funding, or located in jurisdictions with limited fiscal space. A sharp tightening of global financial conditions, a ‘risk-off’ event, could lead to substantial impacts on credit conditions and public finances, especially in emerging market and developing economies, causing large capital outflows, increased risk premia, a rush to safety in the U.S. dollar, and major declines in global activity.

In such a severe downside scenario, global growth could slow to 1 percent this year, with a 15 percent estimated probability of such an outcome. As we navigate this challenging phase with lackluster economic growth, heightened financial risks, and unresolved inflation concerns, policymakers need a steady hand and clear communication.

CONCLUSION

The repercussions of Russia’s war on Ukraine have reverberated not only within the affected nations but also across the region and the globe. This underscores the critical need for a robust global safety net and regional arrangements to cushion economies in the face of such shocks.

In a recent briefing in Washington, IMF Managing Director Kristalina Georgieva emphasized the reality of living in a more shock-prone world. She stressed the importance of collective strength in dealing with the shocks that may arise in the future, recognizing the interconnectedness of nations in addressing global challenges.

While the full extent of the consequences may take years to become clear, there are already evident signs that the war and the subsequent surge in costs for essential commodities will pose challenges for policymakers. Striking a delicate balance between containing inflation and supporting economic recovery from the pandemic will become more arduous for some countries. The increased costs of essential commodities can exacerbate inflationary pressures, complicating the task of policymakers navigating the post-pandemic economic landscape.

In this evolving scenario, the imperative for a global safety net and effective regional arrangements becomes even more pronounced. These mechanisms can provide crucial support to countries grappling with the economic fallout of unforeseen global shocks, emphasizing the interconnected and interdependent nature of today’s world.

BY-SHANNUL H MAWLONG

Source: chat gpt

https://www.imf.org/en/Blogs/Articles/2022/03/15/blog-how-war-in-ukraine-is-reverberating-across-worlds-regions-031522

https://www.imf.org/en/Blogs/Articles/2023/04/11/global-economic-recovery-endures-but-the-road-is-getting-rocky

https://www.imf.org/en/Blogs/Articles/2023/07/25/global-economy-on-track-but-not-yet-out-of-the-woods

https://www.msci.com/www/blog-posts/global-markets-one-year-after/03668219477

NFTs in Music: Transforming the Music Industry.

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A music NFT is a distinct digital asset that is issued on a blockchain and is linked to an individual song, EP, album, or video clip.

Non-fungible tokens (NFTs) have been making waves in the art world, with generative art collections becoming increasingly popular among Web3 enthusiasts and in the traditional art world. However, NFTs as immutable records of ownership for digital items have many more use cases.

While the music industry’s global revenue is expected to surpass $65B in 2023, these earnings predominantly flow into a few large platforms and major record labels. As a result, many artists have started exploring the use of NFTs as a new way of distributing and monetizing music. 

Music NFTs have the potential to revolutionize the way artists create, distribute, and earn income from their music. In contrast to the current model, where artists have to rely on record contracts, brand deals, and extensive touring to advance their careers, music NFTs present artists with the opportunity to generate income solely based on their primary focus—creating music.

In this post, we’ll look at what music NFTs are and how they work and examine how this technology can transform the music industry through improved economics and more immediate fan-artist relationships.

What Is a Music NFT?

First, a quick primer on NFTs. An NFT is a token on a blockchain that is unique. Each NFT has a unique token ID and contract address that sets it apart from other NFTs. While an NFT can be linked to any media, what’s typically associated as the “content” of an NFT is stored in its metadata, which can point to images, videos, music, or other forms of media.

In a nutshell, a music NFT is a distinct digital asset that is issued on a blockchain and is linked to an individual song, EP, album, or video clip. Artists can create unique digital assets as NFTs that represent their music, concert tickets, exclusive merchandise, or virtual experiences, which people can then own, use, or trade. Purchasing a music NFT can be seen as a way of supporting an artist—akin to buying their music directly—while still allowing others to enjoy their work.

Music NFTs enable artists to forge a more direct relationship with their collector community. By helping to circumvent larger platforms, music NFTs give artists the chance to build a more direct connection with their fan base, who can also benefit from new ways of interaction and ownership.

Some music NFTs are generated entirely by an on-chain algorithm with no external dependencies. Generative music posted on-chain empowers artists to create a permanent imprint on an immutable ledger and preserve their creation for future generations exactly as originally intended.

How Do Music NFTs Work?

In essence, music NFTs help shift the ownership of music from companies to individuals. While record labels continue to play an important role in the music industry and can serve several business functions for artists, music NFTs allow artists the option to maintain full ownership of their creations.

Some music NFTs include revenue and royalty-sharing features that can provide a source of income for artists without them having to rely solely on earnings from streaming services, building a large following, or engaging in excessive marketing. Instead, they can rely on a smaller group of highly dedicated fans.

As such, music NFTs can help emerging artists who may not have access to traditional funding or distribution channels. With the rise of Web3 platforms and marketplaces, musicians can independently create and sell their NFTs, giving them greater control over their careers and revenue streams.

Another important benefit is the ability to create token-gated communities that enable fans to participate in exclusive events and promotions, opening up secondary markets for fandom that alter the dynamics of being a fan and enable more integrated fan communities.

How Will Music NFTs Impact the Music Industry?

$0.004 Per Stream Vs. $40 Per Mint

Since the onset of streaming, opportunities for musicians to earn an income have significantly decreased. NFTs turn pieces of music into a commodity, like a piece of art that can be bought and sold, similar to the earlier days of the music industry with vinyl records, cassette tapes, CDs, and MP3s.

Currently, many artists find it difficult to see significant returns on streaming platforms. According to some estimates, one stream on Spotify amounts to about $0.004 paid to the artist, meaning that one million streams net roughly $4000. Getting that many streams isn’t realistic for most independent artists. It’s important to note that the issue here isn’t necessarily with individual companies but more with the underlying economic model. Offering the ability to stream a large portion of the music library of human history for the equivalent of ~$10 a month creates thin margins both for the platforms and the creators, and is likely leading to a race to the bottom.

Real life examples:

  1. Kings of Leon’s NFT Album Release:
    • In March 2021, the American rock band Kings of Leon became one of the first major musical acts to release their album as an NFT. The album, titled “When You See Yourself,” was made available for purchase as three types of NFTs, each offering different perks such as exclusive audiovisual art and a “golden ticket” for VIP concert experiences.
  2. 3LAU’s Ultraviolet NFT Album:
    • Electronic dance music (EDM) artist 3LAU (Justin Blau) released his album “Ultraviolet” as an NFT in February 2021. The NFTs included special edition music and unique experiences, allowing fans to have a more immersive and exclusive connection to the artist.
  3. Beeple’s Collaborations with Musicians:
    • Digital artist Beeple (Mike Winkelmann) has collaborated with various musicians to create NFT-based visual experiences. Notably, his collaboration with EDM artist Deadmau5 resulted in the creation of unique audiovisual NFTs that represented a fusion of music and visual art.
  4. Grimes’ NFT Art and Music Auction:
    • Canadian musician Grimes, known for her experimental music and visual art, auctioned digital art and unreleased music as NFTs. The auction included exclusive pieces of art and audio content, providing fans with a chance to own unique and limited digital assets.
  5. Steve Aoki’s NFT Journey:
    • Renowned DJ and producer Steve Aoki has embraced NFTs as a way to engage with his fan base. He has released NFTs featuring exclusive music, behind-the-scenes content, and virtual experiences. Aoki has also experimented with interactive NFTs, allowing fans to participate in challenges and unlock additional content.

My opinion:

While the potential for NFTs to revolutionize the music industry is evident, it’s crucial to acknowledge the inherent challenges. The tokenization of music rights through NFTs, may introduce complexities in terms of legal frameworks and the fair distribution of revenues.

Additionally, concerns about market volatility and environmental impact raise questions about the long-term sustainability of this trend. While blockchain technology offers direct artist-fan connections, it’s essential to carefully navigate the evolving landscape, considering both the promises and pitfalls of integrating NFTs into the music ecosystem. So, to be honest I’m not a fan of this happening.

Sources:

ChatGpt – version 3.5 ( https://chat.openai.com/share/1086341a-c645-46a5-86e3-9f6049e21891 )

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MACHINE LEARNING AND IT’S BLISS ON NETFLIX

Reading Time: 4 minutes

INTRODUCTION:

As the world’s leading Internet television network with over 160 million members in over 190 countries, our members enjoy hundreds of millions of hours of content per day, including original series, documentaries and feature films. Of course, all our all-time favourites are right on our hands, and that is where machine learning has taken it’s berth on the podium. This is where we will dive into Machine Learning.

MONEY HEIST(2017)

Machine learning impacts many exciting areas throughout our company. Historically, personalization has been the most well-known area, where machine learning powers our recommendation algorithms. We’re also using machine learning to help shape our catalogue of movies and TV shows by learning characteristics that make content successful. Machine Learning also enables us by giving the freedom to optimize video and audio encoding, adaptive bitrate selection, and our in-house Content Delivery Network.

I believe that using machine learning as a whole can open up a lot of perspectives in our lives, where we need to push forward the state-of-the-art. This means coming up with new ideas and testing them out, be it new models and algorithms or improvements to existing ones.

Operating a large-scale recommendation system is a complex undertaking: it requires high availability and throughput, involves many services and teams, and the environment of the recommender system changes every second. In this we will introduce RecSysOps a set of best practices and lessons that we learned while operating large-scale recommendation systems at Netflix. These practices helped us to keep our system healthy:

 1) reducing our firefighting time, 2) focusing on innovations and 3) building trust with our stakeholders.

RecSysOps has four key components: issue detection, issue prediction, issue diagnosis and issue resolution.

Within the four components of RecSysOps, issue detection is the most critical one because it triggers the rest of steps. Lacking a good issue detection setup is like driving a car with your eyes closed.

ALL YOUR FAVOURITE MOVIES AND TV SHOWS RIGHT HERE!

The very first step is to incorporate all the known best practices from related disciplines, as creating recommendation systems includes procedures like software engineering and machine learning, this includes all DevOps and MLOps practices such as unit testing, integration testing, continuous integration, checks on data volume and checks on model metrics.

The second step is to monitor the system end-to-end from your perspective. In a large-scale recommendation system there are many teams that often are involved and from the perspective of an ML team we have both upstream teams (who provide data) and downstream teams (who consume the model).

The third step for getting a comprehensive coverage is to understand your stakeholders’ concerns. The best way to increase the coverage of the issue detection component. In the context of our recommender systems, they have two major perspectives: our members and items.

Detecting production issues quickly is great but it is even better if we can predict those issues and fix them before they are in production. For example, proper cold-starting of an item (e.g. a new movie, show, or game) is important at Netflix because each item only launches once, just like Zara, after the demand is gone then a new product launches.

Once an issue is identified with either one of detection or prediction models, next phase is to find the root cause. The first step in this process is to reproduce the issue in isolation. The next step after reproducing the issue is to figure out if the issue is related to inputs of the ML model or the model itself. Once the root cause of an issue is identified, the next step is to fix the issue. This part is similar to typical software engineering: we can have a short-term hotfix or a long-term solution. Beyond fixing the issue another phase of issue resolution is improving RecSysOps itself. Finally, it is important to make RecSysOps as frictionless as possible. This makes the operations smooth and the system more reliable.

NETFLIX: A BLESSING IN DISGUISE

To conclude In this blog post I introduced RecSysOps with a set of best practices and lessons that we’ve learned at Netflix. I think these patterns are useful to consider for anyone operating a real-world recommendation system to keep it performing well and improve it over time. Overall, putting these aspects together has helped us significantly reduce issues, increased trust with our stakeholders, and allowed us to focus on innovation.

BY: SHANNUL H. MAWLONG

Sources: https://netflixtechblog.medium.com/recsysops-best-practices-for-operating-a-large-scale-recommender-system-95bbe195a841

https://research.netflix.com/research-area/machine-learning

References:

[1] Eric Breck, Shanqing Cai, Eric Nielsen, Michael Salib, and D. Sculley. 2017. The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction. In Proceedings of IEEE Big Data.Google Scholar

[2] Scott M Lundberg and Su-In Lee. 2017. A Unified Approach to Interpreting Model Predictions. In Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett(Eds.). Curran Associates, Inc., 4765–4774.

ChatGPT’s new competitor

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More powerful than ChatGPT': Microsoft unveils new AI-improved Bing and Edge  browser | ZDNET

Bing is an updated Microsoft search service based on artificial intelligence. It’s based on the OpenAI GPT language model, but Bing is newer than ChatGPT 3.5. Microsoft says it’s not just an updated search engine, but a new artificial intelligence-based search channel with a new chat interface that offers better searches, more complete answers and more relevant search results, so readers can spend less time on the page. Artificial intelligence will revolutionize every category of software, including the largest category — search. Bing can also create content and inspire creativity. Microsoft said: “The new Bing can generate useful content. Create a 5-day itinerary for your dream vacation to Hawaii, including links to write emails, book travel and accommodation, prepare for interviews and create quiz questions to help you The new Bing also cites all sources so you can see links to the web content you link to.”

Microsoft has also announced changes to Edge. Artificial intelligence has been added to Edge to help people do more with search and the internet. As for the new Bing search and the new Edge browser, Microsoft highlights some key features:

  • The best search. The new Bing offers an improved version of familiar search, providing more relevant results for simple things like sports scores, promotions and weather, as well as more complete when you need it. It also provides a new sidebar for displaying responses.
  • Full answer. Bing searches the web for results to find and summarize the answers you are looking for. For example, you can get step-by-step instructions on how to replace eggs with another ingredient in your current cake without looking at multiple results.
  • New chat. For more complex searches, such as planning a detailed travel itinerary or choosing a TV to buy, the new Bing offers a new interactive chat. Chat allows you to narrow down your search until you get the full answer you are looking for, asking for details, clarity and ideas. Links are available, so decisions can be made immediately.
  • New Microsoft Edge interface. We have updated the Edge browser with new artificial intelligence features, a new look and added two new features: chat and messaging. Use the Edge sidebar to request summaries of long financial reports to get the main conclusions, use the chat function to request comparisons with competitors’ financial reports, and automatically place them in a spreadsheet. You can also ask Edge to help you create content, such as posts for LinkedIn. Then you can get help updating the tone, format and length of your message. Edge can understand the web pages you are viewing and adapt accordingly.

However, Google issued a warning to its departments, and even the founders and shareholders of the tech giants Larry Page and Sergey Brin stepped up. On Monday, the company introduced its own alternative to ChatGPT called Bard. Google CEO Sundar Pichai called the software an “experimental artificial intelligence service” that is still being tested by a limited number of users and employees of the company and will be released to the general public in the coming weeks.

Microsoft Brings ChatGPT-Like AI Features to Bing, Edge - My TechDecisions

Thus, Bing have been developed to facilitate research and increase their reliability. Starting with the chat mode, you can ask literally any question using an interface very similar to GPT chat, and the answer will be sent in seconds.

Interestingly, when searching for information in real time on the Internet, responses are sent directly from various thematic sites. The source of information for constructing the answer is shown as a footnote, but the user is redirected to the main page of the site in question, and not to the page with the text.

Sources and references: https://blogs.microsoft.com/blog/2023/02/07/reinventing-search-with-a-new-ai-powered-microsoft-bing-and-edge-your-copilot-for-the-web/ https://habr.com/ru/news/t/715508/

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Deepmind’s AlphaCode Satisfactory in a Programming Competition

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Source: Maciek905/Dreamstime stock image

AI code generation systems are a type of artificial intelligence technology that is capable of automatically generating code. These systems have the potential to revolutionize the way software is developed, making it faster and more efficient.

One of the main benefits of AI code generation systems is their ability to save time. These systems can analyze a given problem and automatically generate a solution in the form of code. This can significantly reduce the amount of time it takes for developers to write code from scratch. Additionally, these systems can often generate code that is more efficient and optimized than code written by humans, which can lead to faster and more reliable software.

Another benefit of AI code generation systems is their ability to improve the accuracy and reliability of code. By analyzing a problem and generating a solution, these systems can help eliminate human error that can lead to bugs and other issues in software. This can help reduce the time and resources needed for debugging and testing, which can save money and improve the overall quality of the software.

One of the main challenges of AI code generation systems is their reliance on data. These systems need large amounts of data to learn and generate code, which can be a problem if the data is not available or is of poor quality. Additionally, these systems are only as good as the algorithms and models they are based on, and it can be difficult to design and train these models to generate high-quality code.

Despite these challenges, there has been significant progress in the development of AI code generation systems in recent years. One example is the development of “neural machine translation” systems, which are capable of automatically translating text from one language to another. These systems have been able to achieve impressive levels of accuracy, and they have been widely adopted in a variety of industries.

Another example is the development of “auto-coding” systems, which are capable of generating code for a variety of programming languages. These systems have the potential to significantly reduce the time and effort required to develop software, and they are being explored by a number of companies and organizations.

Examining the abilities of AI code generation systems can be tricky. One means of doing so is to place the system in a programming competition against regular human programmers. A recent experiment of that kind was performed by Deepmind. Deepmind, a subsidiary of Alphabet Inc. is a trailblazing artificial intelligence research laboratory. The experiment was carried out with the use of its AlphaCode deep learning algorithm. AlphaCode converts user input into functioning code by first rewriting it as an action plan. It transforms it into set steps and finally turns it into fully working code. AlphaCode achieved an ‘average’ rating in the competition. A promising acceleration for AI code generation systems.

Overall, AI code generation systems have the potential to revolutionize the way software is developed. These systems can save time and improve the accuracy and reliability of code, and they have already made significant progress in a number of areas. However, there are still challenges to be addressed in terms of data availability and model design, and it will be interesting to see how these systems continue to evolve and improve in the coming years.


Bibliography:

DeepMind. “Competitive programming with AlphaCode.” Deepmind. Published December 8, 2022. https://www.deepmind.com/blog/competitive-programming-with-alphacode

Li, Yujia et al. “Competition-level code generation with AlphaCode.” Science. Published December 8, 2022. https://www.science.org/doi/10.1126/science.abq1158

Kolter, J. Zico. “AlphaCode and “data-driven” programming.” Science. Published December 8, 2022. https://www.science.org/doi/10.1126/science.add8258

Deepmind. “AlphaCode Attention Visualization.” Deepmind. Accessed January 9, 2023. https://alphacode.deepmind.com/

Misogynistic tendencies in AI

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In recent years, artificial intelligence has come under fire for its role in perpetuating and amplifying misogyny. This is primarily due to the fact that AI is often created and trained by male developers, who inadvertently imbue their own biases into the algorithms. As a result, AI systems have been found to display sexist behaviour, such as calling women ‘cooks’ and ‘nurses’ while referring to men as ‘doctors’ and ‘engineers’.

Adele and Betty Friedan as imagined by the Lensa AI.

Sexist language
There are a number of ways in which AI can be misogynistic. One of the most visible ways in which AI perpetuates misogyny is through the use of sexist language. This was most famously demonstrated by Microsoft’s chatbot Tay, which was designed to learn from interactions with users on Twitter. However, within 24 hours of being launched, Tay began tweeting out sexist and racist remarks, which it had learned from other users on the platform.

While this was an extreme example, it highlights the fact that AI systems can easily pick up and amplify the biases that exist in the real world. If left unchecked, this can lead to a reinforcement of sexist attitudes and behaviours.


Algorithmic bias
Another way in which AI perpetuates misogyny is through the use of algorithms. These are the sets of rules that determine how a computer system behaves. Often, these algorithms are designed by humans, who may inadvertently introduce their own biases.
For example, a study by researchers at MIT found that facial recognition systems are more likely to misidentify women as men than vice versa. This is because the system had been trained on a dataset that was predominantly male. As a result, it learned to associate male faces with the concept of ‘person’ more than female faces.
This kind of algorithmic bias can have a severe impact on the real world, as it can lead to women being denied access to certain services or being treated differently by law enforcement.

Data bias
Another issue with AI is that it often relies on data that is biased. This can be due to the fact that the data is collected in a biased way or because it reflects the biases that exist in the real world.
For example, a study conducted by Ellen Broad, an expert in data sharing, infrastructure and ethics, found that Google Photos image recognition system is more likely to label pictures of black people as ‘gorillas’ than pictures of white people. This is because the system had been trained on a dataset that was predominantly white. As a result, it learned to associate black faces with the concept of ‘gorilla’ more than white faces. This kind of data bias can lead to AI systems making inaccurate and potentially harmful decisions. For example, if a facial recognition system is more likely to misidentify black people as criminals, then it could lead to innocent people being wrongly arrested.

Brandee Barker’s Twitter post

Moreover there’s something deeply troubling about the way AI is being used to create ‘portraits’ of people, particularly women. In the case of Brandee Barker, an AI created deeply sexualized versions of the woman.
This isn’t just a case of bad taste or something that can be chalked up to the ‘uncanny valley’ effect. There’s a more sinister element at play here: the objectification and sexualization of women by AI.
It’s not just Barker who has been rendered in a sexualized manner by AI. In an essay for Wired, the writer Olivia Snow wrote that she submitted “a mix of childhood photos and [current] selfies” to Lensa AI and received back “fully nude photos of an adolescent and sometimes childlike face but a distinctly adult body”.
The AI-generated images of women are eerily realistic, and that’s what makes them so troubling. They look like real women, but they’ve been created by machines with the sole purpose of objectifying and sexualizing them. This is a scary prospect, because it means that AI is perpetuating and amplifying the misogyny that already exists in our society.

Addressing the issue
Given the potential impacts of AI-perpetuated misogyny, it is important that the issue is addressed. The solution to this problem is not to try to create AI that is gender-neutral. Instead, we need to ensure that AI systems are designed and built with the needs of all users in mind. This includes ensuring that a diverse range of voices are involved in the development process and that training data is representative of the real world. Only by taking these steps can we create AI systems that are truly inclusive and beneficial for everyone.

Sources:

Lensa AI app

https://www.theguardian.com/us-news/2022/dec/09/lensa-ai-portraits-misogyny

https://www.adweek.com/performance-marketing/microsofts-chatbot-tay-just-went-racist-misogynistic-anti-semitic-tirade-170400/

https://news.mit.edu/2018/study-finds-gender-skin-type-bias-artificial-intelligence-systems-0212

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How a few pixels can cost 69 million USD? A quick jump into NFTs (artNFTs).

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CryptoPunks: Details for Punk #3101
Punk #3101. Sold for 510 ETH ($935,187). Source: https://www.larvalabs.com/cryptopunks/details/3101.

NFT is a pretty controversial topic. Some people say this technology was created to launder money or support terrorism.

How can a digital picture be worth 69 million USD (Beeple NFT)?

The value proposition for NFTs can vary, although the basic idea stays the same. With blockchain technology, we are able to price, monetize and own digital information.

Before blockchain, almost every piece of information (or a bit of information) was stored on a centralized server owned by a big company like Facebook or Google.

When you write a blog post it’s not yours, when you publish a digital artwork its not yours. This problem is especially relevant in the digital art industry, before NFTs there was no way to check the authenticity of digital artwork.

Blockchain is a trustless, distributed public leader which in simple terms means that it is a fully independent, trustworthy and transparent server (anyone can validate any information).

NFT means Non-Fungible Token, it differs from cryptocurrency in the fact that it is unique. One NFT token =! the other one even if the information that it represents is the same.

So what are the advantages of NTFs?

  • Ownership – anyone can own a part of the internet
  • Authenticity – NFTs allow validating the authenticity of a digital information
  • Creation of Economic Opportunity – Ownership is transferable, which means that you can sell or exchange an NFT for anything else. Imagine you are a popular pop star and you write a song. You can make this song an NFT and easily sell for example in a charity auction.

And what are the disadvantages?

  • It isn’t easy to buy an NFT – it requires to setup a cryptocurrency wallet and have knowledge about blockchain technology
  • Creation of an NFT is expensive – it can cost up to hundreds of USD.
  • Price is extremely volatile
  • Most of the projects are scams.

Many of these arguments are a far cry from the objective truth. They more resemble a stereotype than an argument.

Yes, it isn’t easy to buy an NFT or to create it. But the adoption curve is extremely steep and it is getting easier every day. It wasn’t easy to use a spreadsheet in the 1990s too.

The same can be said with respect to the cost of NFT creation. The cost is connected to the very fundamentals of blockchain which at this point has limited transactional capacity, but it is improving. For example, in September there was a major update of the Ethereum blockchain (the most-used blockchain in the world), which improved the number of transactions per second from 15 to a 1000.

Volatility is the price for growth. The faster technology moves the more ups and downs on the road. This is especially relevant to expectations connected to the specific technology. This leads to bubbles and manias like the dot com bubble or NFT bubble in 2021.

Timing Angel Investing Exits with Key Inflection Points | Seraf ...
Hype cycle. Source: https://seraf-investor.com/compass/article/know-when-hold-em-know-when-fold-em-timing-exits-coincide-key-company-inflection-points.

To sum up, in my opinion, NFT technology has unprecedented potential to revolutionise all digital secotrs of the e-economy. Social media, gaming, the creator economy and many more. All the disadvantages are only connected to the status quo of the technology adoption cycle and their significance will decrease with time.

Sources:

  1. https://cryptopunks.app/cryptopunks/details/3101
  2. https://seraf-investor.com/compass/article/know-when-hold-em-know-when-fold-em-timing-exits-coincide-key-company-inflection-points
  3. https://101blockchains.com/advantages-of-nfts/
  4. https://thenftbrief.com/why-are-nfts-bad/
  5. https://medium.com/@qubecryptospace/what-is-nft-and-why-is-it-so-popular-64b3ee62d86a