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Ping Ping Ping That is the sound of my phone alerting me to overnight snowfall at the various Hokkaido ski resorts I monitor. While this sound brings me immense joy in January and February, in March, it brings only FOMO. I decamped from Hokkaido in early March for the past few ski seasons. My recent experience taught me that Mother Nature turns on the heat circa March 1st. I’m a primadonna skier who only likes the driest and deepest pow. However, this season, Gaia changed up big time. There was a brutal warm spell in February that rekt the snow back. The cold weather only returned towards the end of the month. But frigid temperatures came back in March, accompanied by 10 to 30cm dumps of freshie pow pow every night. Hence, the reason why my phone was blowing up. Sitting in various South East Asian hot and humid countries throughout March, I kept foolishly checking the app and ruing my decision to leave the slopes. The April thaw finally occurred in earnest, and with it, the end to my FOMO. As readers know, my ski experiences act as metaphors for my macro and crypto trading book. I previously wrote that the cessation of the US Bank Term Funding Program (BTFP) on March 12th would cause a global market rout. The BTFP was cancelled, but a vicious sell-off in crypto specifically did not occur. Bitcoin broke $70,000 decisively and topped out around $74,000. Solana kept pumping alongside various doggie and kitty meme coins. My timing was wrong, but like the ski season, the unexpected favorable March conditions will not be repeated in April. While I love winter, summer brings joy as well. The onset of northern hemispheric summer brings sporting bliss as I reorient time towards playing tennis, surfing, and kiteboarding. Summer will usher in a renewed gusher of fiat liquidity due to the policies of the US Federal Reserve (Fed) and Treasury. I will briefly outline my mental map on how and why April will experience extreme weakness in risky asset markets. For those intrepid enough to short crypto, the macro setup is favorable. While I will not outright short the market, I have closed in profit several shitcoin and memecoin trading positions. From now until May 1st, I will be in a no-trade zone. I hope to return in May with dry powder ready to deploy to position myself for the bull market to begin in earnest. Tricksters The Bank Term Funding Program (BTFP) ended a few weeks ago, but no US, non-Too-Big-to-Fail (TBTF) banks have subsequently faced any real stress. That is because high priests of fugazi finance have a bag of tricks they will use to surreptitiously print money in order to bail out the financial system. I will peek behind the curtain and explain how they are expanding the USD fiat money supply, which will underpin the general rise of crypto and stonks until the end of the year. While the end result is always money printing, the journey is not without periods where liquidity growth slows, providing a negative catalyst for risk markets. By going through the bag of tricks and estimating when the rabbit will be pulled from the hat, we can guestimate when there will be periods where the free market is allowed to operate. The Discount Window The Fed and most other central banks operate a facility known as the discount window. Banks and other covered financial institutions who are in need of funds can pledge eligible securities to the Fed in exchange for cash. By and large, the discount window, for now, only accepts US Treasuries (UST) and mortgage-backed securities (MBS). Assume that a bank is fucked because a bunch of Pierce & Pierce boomer muppets runs it. The bank holds a UST that was worth $100 when purchased but is currently worth $80. The bank is in need of cash to satisfy deposit outflows. Rather than declaring bankruptcy, the dogshit insolvent bank can tap the discount window. The bank swaps the $80 UST for $80 of dolla dolla bills because under the current rules the bank receives the market value of pledged securities. To deprecate the BTFP and remove the associated negative stigma without increasing the risk of bank failures, the Fed and US Treasury now encourage troubled banks to tap the discount window instead. However, under the current collateral terms, the discount window is not as attractive as the recently expired BTFP. Let’s go back to our example above to understand why. Remember that the UST’s value declined from $100 to $80, which means the bank has an unrealized loss of $20. Initially the $100 of UST was funded with $100 of deposits. But now the UST is worth $80; therefore, the bank would be short $20 if all the depositors fled. Under the BTFP rules, the bank receives par for underwater USTs. That means a UST worth $80, when delivered to the Fed, is swapped for $100 of cash. This restores the solvency of the bank. But the discount window only gives $80 for a UST worth $80. The $20 loss is still there, and the bank remains insolvent. Given that the Fed can unilaterally change the collateral rules to equalize the treatment of assets by the BTFP and discount window, by greenlighting the use of the discount window by the insolvent banking system, the Fed continued the stealth banking bailout. Therefore, the Fed has essentially solved the BTFP problem; the entire UST and MBS balance sheet of the insolvent US banking system (I estimate at $4 trillion) will be supported when needed by money printed to finance loans through the discount window. This is why I believe the markets haven’t forced any non-TBTF banks into bankruptcy post-March 12th, when the BTFP ended. Bank Capital Requirements Banks are often called upon to finance governments who offer bonds at yields less than nominal GDP. But why would private for-profit entities buy something that features a negative real yield? They do it because the banking regulators allow banks to purchase government bonds with little to no money down. When the banks, who hold an insufficient capital cushion against their government bond portfolio, inevitably blow up because inflation appears and bond prices fall as yields rise, the Fed allows them to use the discount window in the manner described above. As a result, banks would rather buy and hold government bonds than lend to businesses and individuals in need of capital. When you or I buy anything using borrowed money, we must pledge collateral or equity against potential losses. That is prudent risk management. But the rules are different if you are a vampire squid zombie bank. After the 2008 Global Financial Crisis (GFC), the world’s banking regulators attempted to force banks globally to hold more capital, thus creating a more robust and resilient global banking system. The system of rules that codified these changes are called Basel III. The problem with Basel III is that government bonds are not treated as riskless. Banks must put a small amount of capital behind their gargantuan portfolio of sovereign bonds. These capital requirements have proven problematic during times of stress. During the COVID March 2020 market crash, the Fed decreed that banks could hold USTs with no collateral backing. This allowed banks to step in and warehouse trillions of dollars worth of USTs in a riskless fashion … at least in terms of their accounting treatment. When the crisis abated, the supplemental leverage ratio (SLR) exemption for USTs was reinstated. Predictably, as UST prices fell due to inflation, banks went bust due to an insufficient capital cushion. The Fed rode to the rescue with the BTFP and now the discount window, but that only covers losses from the last crisis. How can banks step up and slurp down more bonds at the current unattractively high prices? The US banking system loudly proclaimed in November 2023 that due to Basel III forcing them to hold more capital against their government bond portfolios, Bad Gurl Yellen could not stuff them with more bonds. Therefore, something had to give because the US government has no other natural buyers of its debt at these negative real yields. Below is the polite way the banks phrased their precarious situation. Demand for US Treasuries may have softened among several traditional buyers. Bank security portfolio assets have been declining since last year, with bank holdings of Treasuries down $154 billion compared to one year ago. Source: Report to the Secretary of the Treasury from the Treasury Borrowing Advisory Committee Again, the Fed – led by Powell – saved the day. Out of nowhere, at a recent , Powell proclaimed that banks would not be subject to higher capital requirements. Remember that many politicians called for banks to hold more capital so that the regional banking crisis of 2023 would not repeat itself. Obviously, the banks lobbied hard to nullify these higher capital requirements. They had a good argument –  if you, Bad Gurl Yellen, want us to buy dogshit government bonds, then we can only do it profitably with infinite leverage. Banks around the world run every flavour of government; the US is no different. US Senate Banking hearing The icing on the cake was a recent letter from the International Swaps Dealer Association (ISDA) advocating for an exemption of USTs from the SLR I spoke about earlier. In essence, banks can only hold USTs in the trillions of dollars needed to finance the US government deficit on a go-forward basis if they are required to put no money down. I expect as the US Treasury ramps up debt issuance, the ISDA proposal will be accepted. This excellent chart from clearly shows how wasteful the US Government is, as evidenced by the record-high deficit. The two recent periods where deficit spending was higher were due to the 2008 GFC and the boomer-led COVID lockdowns. The US economy is growing, but the government is spending money like it's an economic depression. Bianco Research Taken together, the relaxation of capital requirements and a likely future exemption of USTs from the SLR are a covert way of money printing. The Fed doesn’t print the money, rather the banking system creates the credit money out of thin air and purchases the bonds which then appear on their balance sheet. As always, the goal is to ensure that government bond yields do not rise to a level above the nominal GDP growth rate. As long as real rates remain negative, stonks, crypto, gold, etc., will continue advancing in fiat currency terms. Bad Gurl Yellen My essay “ ” spoke in depth about how the US Treasury, led by Bad Gurl Yellen, increased the issuance of short-term Treasury bills (T-bills) in an effort to drain the trillions of dollars locked in the Fed’s Reverse Repo Program (RRP). As expected, the RRP decline coincided with a rip higher in stonks, bonds, and crypto. But now that the RRP is down to $400 billion, the market is wondering what the next source of fiat liquidity will be that bolsters asset prices. Don’t you worry, Yellen ain’t done yet, shout ‘bout to booty drop. Bad Gurl RRP Balance (white) vs. Bitcoin (yellow) The flow of fiat funds I will discuss focuses on US tax payments, the Fed’s Quantitative Tightening (QT) program, and the Treasury General Account (TGA). The timeline in question is from April 15th (the day tax payments are due for the 2023 tax year) to May 1st. Let me provide a quick guide on their positive or negative impact on liquidity to help you understand the implications of these three things. remove liquidity from the system. That is because payers must remove cash from the financial system by selling securities for example, in order to pay their taxes. Analysts expect tax payments for the 2023 tax year to be on the high side because of the large amounts of interest income received and a solid performance in the stock market. Tax Payments removes liquidity from the system. As of March 2022, the Fed allows roughly $95 billion worth of UST and MBS to mature without reinvesting the proceeds. This causes the Fed’s balance sheet to fall, which we all know reduces dollar liquidity. However, we are not concerned about the absolute level of the Fed’s balance sheet but the pace at which it declines. Analysts, like Joe Kalish of Ned Davis Research, expect the Fed to reduce the pace of QT by $30 billion per month at its May 1st meeting. The reduction in the pace of QT is positive for dollar liquidity as the Fed’s balance sheet rate of decline slows. QT When the balance rises, it removes liquidity from the system, but when it falls, it adds liquidity to the system. When the Treasury receives tax payments, the TGA balance rises. I expect the TGA balance to swell well above the current ~$750 billion level as tax payments are processed on April 15th. This is dollar liquidity negative. Don’t forget it's an election year. Yellen’s job is to get her boss, US President , reelected. That means she must do all she can to juice the stock market to make voters feel rich and ascribe this great outcome to the slow “genius” of Bidenomics. When the RRP balances finally go to zero, Yellen will spend down the TGA, releasing, most likely, an additional $1 trillion of liquidity into the system, which will pump markets. TGA Jeo Boden The precarious period for risky assets is April 15th to May 1st. This is when tax payments remove liquidity from the system, QT rumbles on at the current elevated pace, and Yellen has yet to start running down the TGA. After May 1st, the pace of QT declines, and Yellen gets busy cashing checks to jack up asset prices. If you are a trader looking for an opportune time to put on a cheeky short position, the month of April is the perfect time to do so. After May 1st, it’s back to regular programming … asset inflation sponsored by Fed and US Treasury financial shenanigans. Bitcoin Halving The Bitcoin block reward is forecast to halve on April 20th. This is seen as a bullish catalyst for crypto markets. I agree that it will pump prices in the medium term; however, the price action directly before and after could be negative. The narrative of the halving being positive for crypto prices is well entrenched. When most market participants agree on a certain outcome, the opposite usually occurs. That is why I believe Bitcoin and crypto prices in general will slump around the halving. Given that the halving occurs at a time when dollar liquidity is tighter than usual, it will add propellant to a raging firesale of crypto assets. The timing of the halving adds further weight to my decision to abstain from trading until May. To date I took full profit on these positions, MEW, SOL, and NMT. The proceeds were placed into and staked to earn that phat yield. Before Ethena, I would have held USDT or USDC and earned nothing while Tether and Circle captured the entire T-bill yield. Ethena’s USDe Could the market defy my bearish inclinations and continue higher? Fuck yeah. I’m perennially long as fuck crypto, so I welcome being wrong. Do I really want to babysit my most speculative shitcoin positions while I’m two-stepping at Token2049 Dubai? Hell no. Therefore, I dump. There is no need to be upset. If the dollar liquidity scenarios I discussed above come true, I will have that much more confidence to ape into all manner of dogshit. If I miss a few percentage points of gains but definitely avoid losses for my portfolio and lifestyle, that is an acceptable outcome. With that, I bid you adieu. Please remember to put your dancing shoes on, and I will see you in Dubai for a celebration of the crypto bull market.

Heatwave

তাপপ্রবাহ

Hitzewelle

Ola de calor

Vague De Chaleur

हीटवेव

熱波

폭염

Onda de calor

Волна тепла

Sıcak hava dalgası

Đợt nắng nóng

热浪

Authors: (1) Dominic Petrak, UKP Lab, Department of Computer Science, Technical University of Darmstadt, Germany; (2) Nafise Sadat Moosavi, Department of Computer Science, The University of Sheffield, United Kingdom; (3) Ye Tian, Wluper, London, United Kingdom; (4) Nikolai Rozanov, Wluper, London, United Kingdom; (5) Iryna Gurevych, UKP Lab, Department of Computer Science, Technical University of Darmstadt, Germany. Table of Links Abstract & Introduction Related Work Datasets Examined Manual Error Type Analysis and Taxonomies Automatic Filtering for Potentially Relevant Dialogs Statistical Analysis Evaluation and Experiments Discussion Conclusion, Limitation, Acknowledgments, and References A Integrated Error Taxonomy – Details B Error-Indicating Sentences And Phrases C Automatic Filtering – Implementation D Automatic Filtering – Sentence-Level Analysis E Task-Oriented Dialogs – Examples F Effectiveness Of Automatic Filtering – A Detailed Analysis G Inter-Annotator Agreement – Detailed Analysis H Annotation Guidelines I Hyperparameters and Baseline Experiments J Human-Human Dialogs – Examples E Task-Oriented Dialogs – Examples In Section 6.1, we say that the dialogs of task-oriented datasets considered in our work are of little variety in language and flow. This is most obvious in case of BABI (Bordes et al., 2017) which we want to show using the following example: good morning 1. USER: : hello what can i help you with today SYSTEM : may i have a table with british cuisine in a cheap price range USER : i’m on it. where should it be SYSTEM : madrid please USER : how many people would be in your party SYSTEM : for eight please USER : ok let me look into some options for you 4. SYSTEM : actually i would prefer in paris USER : sure is there anything else to update SYSTEM : instead could it be for four people USER : sure is there anything else to update SYSTEM : instead could it be in a moderate price rang USER : sure is there anything else to update SYSTEM 8. : no USER 8. : ok let me look into some options for you SYSTEM This dialog is prototypical for BABI. The first few turns (the first four in this case) contain the original user request. Then, the user asks for changes (turn five to eight). Overall, the dialogs are very scripted. Users are mostly clear and distinctive in their responses. They contain only little variety in language and flow, which makes them seem very unrealistic. We do not observe a change in this regard across tasks. The following dialog is from SGD (Rastogi et al., 2020): 1. : Our family is planning for a vacation trip. Please can you find a good rental car for a pleasant trip? USER 1. : At what time do you need the car? SYSTEM 2. : I can pick up the car at 15:00 USER 2. : From when onwards you are looking for the rental car? SYSTEM 3. : I need the car from 11th of March. USER 3. : So, how long you need the car? SYSTEM 4. : I might need it till the 13th of this month. USER 4. : Okay! So, where would be your pick up location? SYSTEM 5. : I can pick up the car in Paris on 9th of this month. USER 5. : Okay! There is a nice car, Chevrolet Cruze, a Standard car is available for pick up on March 9th at Charles de Gaulle International Airport. Do you wish to rent this car? SYSTEM 6. : Do you have any other cars for I need the car till 10th of this month. USER 6. : Yup! We’ve 3 more cars. Do you wish to rent Honda Accord, which is a Standard car and its ready for pickup on March 9th from Charles de Gaulle International Airport? SYSTEM 7. : Okay. I go for the Honda Accord. USER The dialog looks much more natural, which might be due to its type. While BABI consists of human-bot dialogs, SGD consists of human-human dialogs. However, the flow is very similar. Up until turn five, the user’s request is refined. Then, the system comes up with a suggestion which the user denies (for a couple of turns) by asking for something different. At some point, user’s agree or disagree on the system’s suggestions. Then the dialog ends. The following dialog is from MWoZ (Budzianowski et al., 2018): 1. USER: Hi, I could use help with my planning. I am trying to find a place to stay. 1. SYSTEM: Ok, to help us find the right place for you lets talk about what you would like. Do you have a price range you prefer? Or an area of town? 2. : I would like it to be in the south and have a rating of 3 stars. USER 2. : We have a moderately priced guesthouse and an expensive hotel that match your requirements. SYSTEM 3. : Does either offer free parking? USER 3. : They both offer free parking and internet. SYSTEM 4. : Okay can you please book it for 7 people for 4 nights starting on Tuesday? USER 4. : Which one? The guesthouse or the hotel? SYSTEM 5. : The hotel, please. USER 5. : Reference number is : BS0ODSGJ. Is there anything else? SYSTEM 6. : Yes, I also need a train from stevenage to cambridge. I want to leave after 10:15 on tuesday. USER 6. : I have train TR0517 that leaves at 11:54. Would that be something that would work for you? SYSTEM 7. : That’s perfect. Could I get the train ID and travel time? USER 7. : The travel time is 49 minutes. SYSTEM 8. : Great, that’s all I need, thanks so much for your help! Have a great day! USER 8. : You’re very welcome! Thank you! Bye! SYSTEM Like in case of SGD, the dialog looks very natural. However, in contrast to BABI and SGD, the dialogs consist less of refinements, but more of multiple tasks as shown in this example. First, the user asks for a hotel in a city, then he asks for transportation to that city. Sometimes, he also asks for locations with entertainment. While the first request is usually completed (the booking of a room in this case), the second request is usually about gathering information (the user just asks for the train number, departure and travel time, but not for booking a seat). This paper is under CC BY-NC-SA 4.0 DEED license. available on arxiv

Examples of Task-Oriented Dialogs 

Portfolio Management: All The Ways AI Is Transforming Modern Asset Strategies

পোর্টফোলিও ম্যানেজমেন্ট: সমস্ত উপায় এআই আধুনিক সম্পদ কৌশলগুলিকে রূপান্তরিত করছে

Portfoliomanagement: Wie KI moderne Anlagestrategien verändert

Gestión de carteras: todas las formas en que la IA está transformando las estrategias de activos modernas

Gestion de portefeuille : toutes les façons dont l'IA transforme les stratégies d'actifs modernes

पोर्टफोलियो प्रबंधन: वे सभी तरीके जिनसे AI आधुनिक परिसंपत्ति रणनीतियों को बदल रहा है

ポートフォリオ管理: AI が現代の資産戦略をどのように変革しているか

포트폴리오 관리: AI가 현대 자산 전략을 변화시키는 모든 방법

Gerenciamento de portfólio: todas as maneiras pelas quais a IA está transformando as estratégias modernas de ativos

Управление портфелем: все способы, которыми ИИ трансформирует современные стратегии управления активами

Portföy Yönetimi: Yapay Zekanın Modern Varlık Stratejilerini Dönüştürdüğü Tüm Yollar

Quản lý danh mục đầu tư: Tất cả các cách AI đang chuyển đổi các chiến lược tài sản hiện đại

投资组合管理：人工智能正在改变现代资产战略

A Dozen (or so) Learnings From 15 Years of Software Incident Management

সফ্টওয়্যার ঘটনা ব্যবস্থাপনার 15 বছর থেকে এক ডজন (বা তাই) শিক্ষা

Ein Dutzend (oder so) Erkenntnisse aus 15 Jahren Software-Vorfallmanagement

Una docena (más o menos) de aprendizajes de 15 años de gestión de incidentes de software

Une douzaine (ou deux) d'enseignements tirés de 15 ans de gestion des incidents logiciels

सॉफ्टवेयर घटना प्रबंधन के 15 वर्षों से एक दर्जन (या लगभग) सीखें

15 年間のソフトウェア インシデント管理から学んだ 12 の教訓

15년간의 소프트웨어 사고 관리 경험을 통해 얻은 12가지 정도의 교훈

Uma dúzia (ou mais) de aprendizados de 15 anos de gerenciamento de incidentes de software

Дюжина (или около того) уроков за 15 лет управления инцидентами с программным обеспечением

15 Yıllık Yazılım Olay Yönetiminden Bir Düzine (ya da O Kadar) Ders

Hàng chục (hoặc hơn) bài học từ 15 năm quản lý sự cố phần mềm

从 15 年的软件事故管理中学到的十几个经验

In the presentation below, Yaron Velner, founder of , presented the challenges of mitigating the human factor in DeFi risk management and how to leverage on-chain risk feeds to build trust in DeFi platforms. B Protocol https://youtu.be/p2dbLHpSe_Q?si=IeewOG5_1_1x8Ota&embedable=true Below is a glossary of key concepts mentioned during Yaron’s talk, intended as a supplement to his video presentation. About B Protocol has been building open-source protocols and infrastructure for risk mitigation and assessment for the DeFi ecosystem since 2020. Through our research arm, , and its novel risk framework, we have supported over a dozen DeFi protocols with risk analysis, research, audits, and monitoring. B Protocol RiskDAO Our and formula automate the process of setting risk parameters for lending platforms in a transparent way, building the next generation of DeFi risk management infrastructure. Risk Oracle SmartLTV Risk Oracle B. Protocol’s risk oracle is an on-chain decentralized system that provides objective risk-related information about different assets, protocols, or platforms within the DeFi ecosystem. The oracle assesses objective risk-related parameters, such as liquidity and volatility of assets, borrowing and lending caps, liquidations at risk, existing bad debt, smart contract audits, and updates, etc. Platforms and users can utilize the data provided to make informed decisions regarding listing and managing their lending markets, setting risk parameters that are aligned with the platform’s subjective risk appetite. More information about the risk oracle can be found in B. Protocol’s . documentation LTV Ratio LTV is an acronym for Loan-To-Value ratio. It is a measure of the ratio of a user’s loan to the value of their collateral, and it is the DeFi equivalent of a credit score in traditional finance. LTV is a vital metric for gauging the risk and security of loans in the DeFi ecosystem, and loans are often overcollateralized to reduce the likelihood of losses due to defaults, market volatility, or sudden declines in collateral value. LTV ratio is typically expressed as a percentage and calculated using: When a user’s LTV rises above a predefined threshold, occur. forced liquidations Risk Appetite Risk Appetite is commonly defined as the amount and type of risk that an organization is willing to accept or assume. This appetite can vary from platform to platform and from DAO to DAO as they each have their perspective on what is to be considered as risky. Currently, most risk assessment frameworks in DeFi combine and mash this subjective, qualitative risk appetite with objective and measurable risk-related data feeds. B.Protocol separates the two through its SmartLTV formula that calculates the LTV based on objective data together with a risk level factor that represents the subjective risk appetite. The risk level factor is a single numerical value that aims to represent a desirable safety margin by accounting for potential deviations from previously observed stats to anticipated values in black swan events. For instance, it considers scenarios where volatility could be three times higher than what was previously recorded. Ultimately, this factor enables lending protocols to tailor their risk management strategies to their specific goals and tolerances while empowering users with the transparency necessary to make informed decisions. Circuit Breakers Circuit breakers are mechanisms that temporarily halt or limit specific activities or trading within a protocol or platform to manage extreme market volatility or prevent sudden crashes. The mechanism is triggered by predefined conditions, such as rapid price declines, high volatility, or abnormal trading volumes. Once activated,  circuit breakers halt activities like trading, lending, borrowing, or other relevant operations to prevent insolvency, protect users from losses, and offer time for the market to stabilize. B.Protocol’s risk oracle and its first implementation – the which is already live on mainnet – can be used as an automated circuit breaker on lending platforms, triggered by rapid market movements or malicious setup of risk parameters. SmartLTV formula Learn more about B Protocol here: B Protocol Website B Protocol Documentation B Protocol Twitter Yaron Velner Twitter The Blockchain Oracle Summit is the world’s only technical summit that dives deep into the use cases, limitations, and impacts of oracles on the wider blockchain ecosystem. Leading speakers worldwide gathered in Paris to share their work and experience building and using Oracle solutions. Article by . Michael Abiodun

How to Remove the Human Factor From DeFi Risk Management: The Key Concepts to Know

ডিফাই রিস্ক ম্যানেজমেন্ট থেকে মানব ফ্যাক্টরকে কীভাবে সরিয়ে ফেলা যায়: জানার মূল ধারণা

So entfernen Sie den menschlichen Faktor aus dem DeFi-Risikomanagement: Die wichtigsten Konzepte, die Sie kennen sollten

Cómo eliminar el factor humano de la gestión de riesgos de DeFi: los conceptos clave que debe conocer

Comment supprimer le facteur humain de la gestion des risques DeFi : les concepts clés à connaître

डेफी जोखिम प्रबंधन से मानवीय कारक को कैसे हटाएं: जानने योग्य मुख्य अवधारणाएं

DeFiリスク管理から人的要因を取り除く方法: 知っておくべき重要な概念

DeFi 위험 관리에서 인적 요소를 제거하는 방법: 알아야 할 주요 개념

Como remover o fator humano do gerenciamento de risco DeFi: os principais conceitos a saber

Как исключить человеческий фактор из управления рисками DeFi: ключевые понятия, которые следует знать

İnsan Faktörü DeFi Risk Yönetiminden Nasıl Çıkarılır: Bilinmesi Gereken Temel Kavramlar

Cách loại bỏ yếu tố con người khỏi quản lý rủi ro DeFi: Các khái niệm chính cần biết

如何从 DeFi 风险管理中消除人为因素：需要了解的关键概念

What’s your spiciest opinion about product management? I scoured the Twitter streets and found a few interesting ones to react to. Let me know what your thoughts are in the comments! Roadmaps are a waste of time Carl Vellotti on Twitter kicks us off with a classically spicy topic in the PM world: roadmaps. It’s an age-old topic. Business wants reasonable expectations and clarity, product needs to remain flexible and is painfully aware that timelines don’t work. So, what do we do? I am required to produce roadmaps in my current role. I use the three following tactics to ensure maximum alignment: I break down the roadmap into four quarters. Any timeframe shorter than that is suicide. With every roadmap communication (e.g. email, meetings, etc.) I remind everyone that a roadmap is not a plan. The further to the right you look, the less ‘plan’ it even is. I try as much as possible to reduce the workload and keep available time in each quarter to be flexible. Data breeds average products Amit says the quiet thing out loud and I’m here for it. It’s always hard to go against the ‘data-backed’ crowd. They have science and research on their side, right? How could that be wrong? My overall problem with this is mostly semantics. Most people or organisations claim to be ‘data-driven’ which I think is wrong for a few reasons: They likely don’t have enough data (unless they’re Google/Facebook). The data that drives them is biased (researcher bias, retrofitting research to the CEO’s already made-up mind, etc.). They use the pretence of ‘data’ to justify a decision and never again critically look at it. Instead, I’ll always advocate a data-informed approach. It’s subtle, but it makes a world of difference. Being data-informed means you’re aware the data collected might be insufficient, biased, and could completely be skipped during decision-making. A data-informed PM with great product sense and the gut to make decisions is the true winning formula. SCRUM is bad for velocity I wrote a 6-part series on moving away from a SCRUM-ish approach to product. Clearly, I agree with this take. : Read Moving from SCRUM-ish to Shape Up. Build first, problem second Ugh. I don’t know man. This one’s tough. I can’t picture myself working on any product, project, or even feature that wasn’t initiated by some sort of problem. Even if you’re hoping to build something brand new, something creative, something you dreamt of, surely it still stems from some sort of problem, right? Problem → Solution. That’s the cornerstone of what we do as product people and, dare I say, entrepreneurs. I guess it is a spicy take! Frameworks are training wheels for dummies I have a bone to pick with frameworks and it feels good to see others seem to agree. I don’t dismiss frameworks entirely. They can provide useful inspiration (in the same way a case study or a template can). My problem is when frameworks are sold as solutions to problems. Often, they don’t even provide anything of value. Take the : RACE Framework This framework is meant to teach us that to get customers you should: Reach customers Get them to act Convert a few of them Engage them I’m confident a 6 year old with a lemonade stand could tell you this. And without the fancy words, even better. That’s my quota of old-man-yells-at-clouds for today. What are your spicy PM opinions? Want to read more? I went deeper into each on my Substack. unpopular PM opinion

5 Spicy Product Management Takes

5 মশলাদার পণ্য ব্যবস্থাপনা লাগে

5 pikante Produktmanagement-Tipps

5 pasos para la gestión de productos picantes

5 étapes de gestion des produits épicés

5 मसालेदार उत्पाद प्रबंधन लेता है

5 つの重要な製品管理の取り組み

5가지 매운 제품 관리 요령

5 etapas picantes de gerenciamento de produtos

5 острых приемов управления продуктом

5 Baharatlı Ürün Yönetimi Gerekir

5 bước quản lý sản phẩm cay

5 个辣味产品管理要点

When it comes to the increasingly fast-paced world of marketing, effective project management is the key to long-term success. However, with a plethora of options available, selecting the right software for your business can be a daunting task. In this blog, we'll explore the essential factors to consider when choosing the best marketing project management software for your unique needs. Assess Your Marketing Workflow and Team Dynamics The first step in choosing the right is understanding your business's unique needs and workflow. Start by assessing the intricacies of your marketing campaigns, team dynamics, and the specific challenges you face. marketing project management software Consider factors such as the size of your team, the nature of your projects, and the collaboration requirements. Understanding these aspects will guide you in identifying the features and functionalities that are critical for your business. Features to Look For: Task Management and Planning Efficient task management is the foundation of successful marketing project execution. Look for software that allows you to create, assign, and track tasks seamlessly. Gantt charts and project timelines can provide a visual representation of project progress and help in identifying bottlenecks. Collaboration Tools Robust collaboration features are essential for teams working on marketing projects. Look for project management software for marketing that facilitates real-time communication, file sharing, and feedback loops. Integrated chat, discussion boards, and comment threads within the project management tool can also significantly enhance collaboration with both team members and external stakeholders. Resource Allocation and Tracking Ensure the PM software allows you to allocate resources efficiently, including tracking workloads, in order to prevent any burnout among team members. By making the most of resource management features, you can help when it comes to optimizing team capacity and ensuring that everyone is working on tasks that align with their skills and expertise – also a key factor in enabling job satisfaction. Integration Capabilities Seamless integration with other tools your marketing team uses is crucial for a cohesive workflow. Look for project management software that integrates with popular marketing tools, CRM systems, and communication platforms. Integration with email marketing software, design tools, online proofing, and analytics platforms can streamline processes and improve overall efficiency. Customization Options A one-size-fits-all approach might not suit the unique requirements of your marketing projects. Choose software that allows for the customization of workflows, task lists, and project structures. The ability to tailor the software to match your team's specific needs can significantly improve adoption and effectiveness. Consider Scalability and Future Growth As your business expands, so will your marketing initiatives. It's crucial to choose a marketing project management software that can scale with your business. Consider the software's capacity to accommodate growing teams, increasing project complexity, and evolving workflows. Scalability ensures that the software remains an asset rather than a hindrance as your business matures. User-Friendly Interface and Adoption No matter how feature-rich a marketing project management software is, it's only valuable if your team adopts it seamlessly. Opt for a platform with an intuitive and user-friendly interface to reduce the learning curve. Conducting user onboarding and training sessions, and providing adequate support during the transition can facilitate smoother adoption. Additionally, consider platforms that offer mobile accessibility, enabling your team to stay connected and productive on the go- essential in an increasingly remote-working world. Budgetary Constraints and Return on Investment (ROI) While it's tempting to opt for the software with the most extensive feature set, it's crucial to align your choice with your budget constraints. Evaluate the pricing models of different software solutions and consider the long-term ROI. Some platforms offer tiered pricing based on the number of users or projects, while others may have a flat-rate model. Be mindful of any hidden costs and ensure that the chosen software provides tangible value for your investment. Security and Compliance Given the sensitive nature of marketing data and campaigns, security should be a top priority when selecting project management software. Look for platforms that prioritize data encryption, secure user authentication, and compliance with industry regulations. Ensure that the software adheres to data protection standards and offers features like role-based access control to safeguard sensitive information. Evaluate Customer Support and Training Effective customer support can be a lifesaver when encountering issues or during the initial onboarding phase. providers that offer responsive customer support, comprehensive documentation, and training resources. Aproove’s work management software Assess the availability of tutorials, webinars, and user forums to facilitate ongoing learning and troubleshooting. Choosing the best marketing project management software for your business requires a careful analysis of your unique needs, team dynamics, and project requirements. By focusing on features such as task management, collaboration tools, resource allocation, integration capabilities, customization options, scalability, user-friendliness, budget considerations, security, and customer support, you can make an informed decision that aligns with your business goals. Remember that the right software is not just a tool; it's a strategic asset that empowers your team to navigate the complexities of the digital marketing world successfully.

How to Choose the Best Marketing Project Management Software for Your Business

আপনার ব্যবসার জন্য সেরা মার্কেটিং প্রজেক্ট ম্যানেজমেন্ট সফ্টওয়্যার কীভাবে চয়ন করবেন

So wählen Sie die beste Marketing-Projektmanagement-Software für Ihr Unternehmen aus

Cómo elegir el mejor software de gestión de proyectos de marketing para su empresa

Comment choisir le meilleur logiciel de gestion de projet marketing pour votre entreprise

अपने व्यवसाय के लिए सर्वश्रेष्ठ मार्केटिंग प्रोजेक्ट प्रबंधन सॉफ़्टवेयर कैसे चुनें

あなたのビジネスに最適なマーケティング プロジェクト管理ソフトウェアを選択する方法

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Leveraging AI in Learning Management Systems ChatGPT and its counterparts had an extraordinary impact on many industries, including the education sector. All of a sudden, instructors had an effective way to make engaging learning materials, quizzes, and tests with no extra costs. OpenAI’s solution has shown a glimpse into the world where no geographical, language, or financial barriers prevent students from getting a quality education. And they’re putting the new tools to good use. Currently, 21% of educators , with 4% building entire lesson plans with its help. While those numbers are modest, they show just that AI solutions are becoming a part of the learning experience. Content creation isn’t the only area where this technology has found a good footing. use the chatbot to make assignment prompts Artificial intelligence solutions are gaining momentum in easing the administrative work of educational organizations. The most prominent example of integration can be seen in new AI-based learning management systems. Let’s take a look at the use of this advanced technology in LMS products and what the future holds for this partnership. Overview of Learning Management Systems (LMS) Private companies and learning institutions need a straightforward way to store and work with educational data. Being able to quickly access personal information, academic progress, reports, and tasks is crucial for successful training. Learning management system features let organizations handle these operations without installing additional software. The market for these solutions is always on the rise. Between 2025 and 2030, it's from $28,1 billion to $70 billion. This year, the number of LMS users has reportedly reached 73,8 million, with this figure showing to signs of stopping. expected to grow What makes these products particularly useful is the number of features they possess, but we’ll talk about those a bit later. Of course, LMS products can’t actually provide education on their own. They require hardware, people who know the ins and outs of educational theory, and software products like Skype or Google Meet to teach learners. The basic setup looks like this: a laptop, an LMS like Blackboard, and an instructor. These components help private companies and educational institutions to manage the learning process successfully. Modern learning management systems can be roughly divided into two types: corporate and institutional. Depending on how sophisticated these programs are, they support the following features: . Learning management systems help educators build the course content. In addition to texts and interactive tests, these materials can include charts, graphs, and videos. Course management . Many LLMs have a dashboard showing how well students or company employees handle their courses. They provide data on attendance, likelihood of success, and completion rates. These metrics identify potentially failing individuals and offer aid with their academic pursuits, ala something out of Minority Report. Academic performance tracking . Modern LMS products automate learner assessment through online tasks and exams. With their help, it's possible to submit assignments and complete online quizzes. Online grading . Advanced systems allow students to share feedback with their peers and teachers. This information helps educators adjust their approach and point out areas where students need to improve. Feedback . Some LMSs use collective and individual content, such as slideshows, online lectures, live discussions, pre-recorded videos, and reading assignments, offering a more comprehensive educational experience. Asynchronous and synchronous learning Common Types of LMS Currently, there are seven types of learning management systems organizations can use. Their choice depends on the end goal of the educational process and the requirements of individual companies and institutions. products offer a more laid-back approach when it comes to maintenance and updates. The organization pays for the solution, and its developers handle the rest. This lets educators focus on their academic goals. Closed-source LMS Their counterpart, the , are a shoo-in for institutions that know their way around code. These are highly customizable, with engineers being able to add or remove some of their features. In extreme examples, it's possible to tailor products to individual needs and requirements. open-source LMSs Organizations with 500+ employees on their staff can work with . Such products often come with additional features. These include a discussion board, gamification elements, team learning tools, an analytical suite, and multi-user access to study materials. enterprise systems Additionally, organizations can work with . These are perfect for adopters with zero technical expertise. It’s also a wise choice when institutions require courses built from the ground up, using their practices as a major element of the learning process. solutions offering authoring tools The safest, but probably the hardest to integrate types, has to be . Organizations need to add those on their servers and within the confines of their physical locations. These products make up for the complicated installation and updating process thanks to their high customizability and privacy measures. installed LMS The last two types on our list are and LMS solutions. As their names suggest, one of these products can be paired with other pieces of software, while the others don’t support this feature. compatible non-compatible In the first case, the LMSs can be paired with apps like Zoom, Google Meet, and BambooHR. In the second, applications usually provide all of the basic features but cannot integrate with other solutions. Understanding AI in Learning Management Systems Modern-day LMS solutions help educators organize and deliver course materials. But, they mostly offer the same learning path for all students, which may not be the optimal approach for educators. Luckily, the rise of artificial intelligence means there’s an alternative to one-size-fits-all products. LMS products now have the capacity to think on a level close to humans instead of being mindless information repositories. While this isn’t replicant-level intelligence, it lets LMS solutions understand and analyze information, make predictions, and answer requests. In the edtech environment, AI-based solutions handle daily operations and aid in improving the learning processes. Here’s how standard LMS products compare to AI-based solutions. Basic LMS AI-based LMS . All students learn the same type of content together. Standardized learning . The experience evolves and adapts based on individual progress. Dynamic learning . Access to standard analysis information. Basic analytics . Give deep insights that lead to more accurate decisions. Deep insights . Provide the same content with no regard for individual learning styles. Static content . Offer tailored materials that are unique to individual style and pace. Personalized content . No engagement outside of standard learning content. Limited interactivity . Student education aligns with individual requirements. Interactive environment AI Components Used In LMS Solutions Advanced learning management systems don’t use all types of AI under the sun. Several artificial intelligence components allow applications to perform specific tasks. . LMS products use this tech to extract information from large data sets. This provides insights into student learning patterns, performance, and engagement. Data mining . With deep learning, these systems analyze vast amounts of information to recommend relevant content, convert spoken language to text, and describe images for the visually impaired. Deel learning . This technology allows LMS products to learn and improve from experience. These features lead to tailored content recommendations and analysis patterns in student data that predict academic outcomes. Machine learning . The NLP area of comprehend, interpret, and produce human speech. LMS programs use it to provide answers, guidance, feedback, and grades. Natural language processing artificial intelligence lets educational solutions . This technology helps systems interpret and classify emotions in textual data. They tell if students are happy, confused, or frustrated with the course materials. Instructors use this information to improve the educational process. Sentiment analysis Top AI Applications And Benefits in LMS Solutions have several applications that enhance the learning experience for educators and students alike. AI-based edtech solutions . AI components used in LMS products streamline student enrollment, schedule management, and reporting. This lets educators focus on more pressing tasks like improving the learning content. Administrative automation . Artificial intelligence algorithms evaluate written essays, responses, and tests in mere seconds. They provide personal feedback, pointing out areas where the individual’s knowledge can be improved. Automated grading and feedback . LMS solutions based on AI adapt content to people with disabilities. For example, by turning text into audio files for those with poor eyesight. Better accessibility . These products improve the work between students and educators. For example, they offer discussion topics or moderate them to keep the collaborations respectful and productive. Enhanced collaboration . With AI-based LMSs, it's possible to provide one-on-one study assistance. Instead of waiting for instructors, students receive guidance on problem-solving, notions, and subjects. Intelligent tutoring . AI algorithms analyze academic performance, preferences, and pace to create individual content. This keeps students engaged and helps them better comprehend the learning materials. Personalized learning . In LMS products, artificial intelligence components predict outcomes based on student performance, engagement, attendance rates, and other factors. This analysis helps identify people at risk of failing courses or dropping out. Predictive analytics . Finally, AI-enhanced learning management systems allow for making unique materials, tests, quizzes, and study objectives based on a person’s current understanding of courses. Tailored content creation What The Future Holds For AI in LMS Currently, learning management systems are heavily influenced by advancements in various artificial intelligence sectors. In addition to this progress, several technological trends will dictate the next steps in these solutions. In the future, AI-based LMS products will use gamification techniques to offer a more immersive, motivational, and engaging learning experience. They will make education more effective and enjoyable through competition, rewards, and collaboration. Apps like Duolingo, Kahoot, and Quizlet already use these techniques and show their merit. The use of AI in LMS solutions will drive further cooperation among students. LMS products will be able to recommend peers and study groups for a more productive education process. Learning management systems will also use social features like real-time messaging, discussion forums, and video talks, making the learning environment more interconnected. Finally, the widespread integration of AI tech into LMS products will lead to an extremely tailored educational experience for all participants. This is going to improve academic outcomes and higher graduation rates. The best part is that the solutions will provide a tailored education process and adjust it without additional expenses on the part of the organizations. Conclusion The advancements shown by the modern examples of AI-based LMS products uncover the potential for high-quality education that isn’t only practical but affordable and streamlined for students and organizations involved in the learning process. An adaptable learning process will help deal with the rigid educational system and open learning for people with all kinds of needs and preferences. Would you like to take a stab at answering some of these questions? The link for the template is . Interested in reading the content from all of our writing prompts? Click . HERE HERE

How to Leverage AI in Learning Management Systems

লার্নিং ম্যানেজমেন্ট সিস্টেমে কীভাবে এআই ব্যবহার করা যায়

So nutzen Sie KI in Lernmanagementsystemen

Cómo aprovechar la IA en los sistemas de gestión del aprendizaje

Comment tirer parti de l'IA dans les systèmes de gestion de l'apprentissage

लर्निंग मैनेजमेंट सिस्टम में एआई का लाभ कैसे उठाएं

学習管理システムで AI を活用する方法

학습 관리 시스템에서 AI를 활용하는 방법

Como aproveitar a IA em sistemas de gerenciamento de aprendizagem

Как использовать ИИ в системах управления обучением

Öğrenim Yönetim Sistemlerinde Yapay Zekadan Nasıl Yararlanılır?

Cách tận dụng AI trong hệ thống quản lý học tập

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