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Miss this week’s AI news and you might just fall behind.AI_Distilled #96: What’s New in AI This WeekYou can now run and fine-tune Qwen3 and Meta's new Llama 4 models with 128K context length & superior accuracy. Unsloth is an open-source project that allows easy fine-tuning of LLMs and that also uploads accurately quantized models to Hugging Face. GitHub repo: https://github.com/unslothai/unslothUnsloth's new Dynamic 2.0 quants outperform other quantization methods on 5-shot MMLU & KL Divergence benchmarks, meaning you can now run + fine-tune quantized LLMs while preserving as much precision as possible. Read more here . Tutorial for running Qwen3 here.Tutorial for running Llama 4 here.Welcome to another exciting edition of our AI_Distilled! This week, we're witnessing a surge in innovative AI solutions, with companies like OpenAI and Microsoft rolling out tools that streamline development and enhance user interaction. From Apple opening its models to developers to the fierce competition for AI's top talent, join us as we explore the latest breakthroughs shaping our digital world.LLM Expert Insights,PacktIn today's issue:📅 June’s AI Must-Attends: From AI Engineer World’s Fair to Packt’s Agent Bootcamp—here are 6 events you don’t want to miss this month.🔌 MCP, Explained: Paul Singh breaks down the Model Context Protocol—your plug-and-play solution for seamless AI tool integration.💻 Codex Arrives: OpenAI rolls out Codex, a powerful AI coding agent for writing features, fixing bugs, and navigating codebases.🧠 Windows Gets Smarter: Microsoft integrates native MCP into Windows and launches AI Foundry for seamless agent automation.🎟️ Google AI Ultra Drops: A new $249.99/mo subscription offers Gemini upgrades, cinematic video tools, and 30TB of storage.🍏 Apple Opens Up: Developers may soon build apps with Apple’s AI models—announcement expected at WWDC 2025.🏁 AI Talent Wars: OpenAI, Google & more compete for elite researchers—offering private jets and millions in perks.👨‍💻 Copilot’s New AI Agent: GitHub's upgraded Copilot now tackles coding issues with draft PRs, vision models, and full MCP support.🎧 On-Device Audio AI: Stability AI & Arm launch a mobile-ready model for text-to-audio generation—11 seconds of sound in 8.📈EXPERT INSIGHTSJUNE'S MUST ATTEND AI/LLM EVENTSIn June 2025, a number of exciting AI conferences are already generating buzz. Here are the Top 5 not-to-miss events in the next month (for more information and registration details, please visit the links):1. AI Engineer World’s FairDate: June 3–5, 2025Location: San Francisco, California, USACost: $299–1,799 in-personThe AI Engineer World's Fair, from June 3-5, 2025, in San Francisco, is the largest technical conference for AI engineers. It would host approximately 3,000 attendees, featuring 150 talks and 100 practical workshops. Topics include Generative AI, AI agents, LLMs, infrastructure, and AI in Fortune 500 companies, offering unparalleled networking and learning opportunities for industry professionals.2. Data + AI SummitDate: June 9–12, 2025Location (Hybrid): San Francisco, California, US, and available online.Cost: $1,395–1,895 in-person. Free for virtual admission. Discounted tickets are available with group-rate pricing.The Data + AI Summit is a four-day event hosted by Databricks. It includes panel discussions, networking opportunities, and training workshops on topics such as data engineering, data governance, and machine learning.3. The AI Summit LondonDate: June 11–12, 2025Location: Tobacco Dock, London, UKCost: £125–2,499AI Summit London, spanning over two days, will cover a wide range of topics including agentic AI in action and ethical use of AI. With a strong lineup of sponsors and thousands of guests, the summit offers great opportunities for networking with leading AI practitioners.4. Packt’s AI Agent Bootcamp (Build AI Agents Over the Weekend)Date: June 21–22 and 28–29, 2025Location: Live Virtual WorkshopCost: Our AI Agent Bootcamp aims to equip developers, ML engineers, data scientists, technical professionals, and software architects with the practical skills to design, build, and deploy AI agents using frameworks like LangChain, AutoGen, and CrewAI, moving from theoretical understanding of LLMs to practical application.5. CDAO GovernmentDate: June 25–26, 2025Location: Washington, D.C., USCost: $499 in-person; Free for VP and C-level government executives.The CDAO Government conference in Washington, D.C., is unique as it unites U.S. government data leaders to explore AI, governance, and ethical data use in public services. Celebrating its 13th anniversary, this event offers an excellent opportunity to learn how to securely leverage AI's capabilities for government data challenges.This was just a quick peek into spaCy pipelines — but there’s much more to explore.For instance, the spacy-transformers extension integrates pretrained transformer models directly into your spaCy pipelines, enabling state-of-the-art performance. Additionally, the spacy-llm plugin allows you to incorporate LLMs like GPT, Cohere, etc. for inference and prompt-based NLP tasks.Master AI Tools, Set Automations & Build Agents – all in 16 hours (for free)AI is no longer just a buzzword — it’s the most valuable skill of this decade– to make money, to get hired and to be future-paced.That’s why, you need to join the 2-Day Free AI Upskilling Sprint by Outskill which comes with 16 hours of intensive training on AI frameworks, tools and tactics that will make you an AI expert.Originally priced at $499, but the first 100 of you get in for completely FREE! Claim your spot now for $0! 🎁📅23rd May- Kick Off Call & Session 1✅Live sessions- 24th & 25th May🕜11AM EST to 7PM ESTJOIN NOW(Limited Free Seats! 🚨)EXPERT INSIGHTS BY PAUL SINGHModel Context Protocol (MCP) and what it means for youIf you're working on AI design or tool integration, the Model Context Protocol (MCP) offers a seamless, standardized way to connect AI tools, data sources, and LLM applications. Developed by Anthropic, MCP is an open protocol designed to simplify the often complex and time-consuming process of integrating rapidly evolving AI models with tools and services. Think of it as the USB-C of the AI world—plug-and-play, regardless of the LLMs or tools you're working with, and without diving into the intricate technicalities of MCP itself.MCP operates on a client-server model, where your LLM application runs a local MCP client that communicates with one or more MCP servers. A service provider only needs to implement a single MCP server, which can then handle APIs, databases, and other services, without requiring constant code adjustments for each new integration.Take a look at how three different MCP servers integrate with APIs and services:MCP leverages the lightweight JSON-RPC message format (a simple remote procedure call protocol), stateful connections, server-client capability negotiation, and reflection. Reflection allows the client to query the server about its capabilities, which can then be surfaced to the LLM automatically via the orchestrating application’s prompt.When designing with MCP, it's important to keep your architecture modular, test each component thoroughly, document your iterations, and ensure security by validating inputs and controlling access.MCP is gaining traction with large organizations like Microsoft, which is integrating it into key products such as Semantic Kernel, Copilot Studio, and GitHub Copilot. I envision a near future where MCP-as-a-Service becomes the de facto standard, eliminating deployment overhead and enabling seamless AI-to-AI or agent-to-agent communication. For example, MCP endpoints could allow straightforward integration without server management, while internal repositories of MCP clients could democratize standardized tool access across organizations.To read more about MCP, you can check out these resources: https://modelcontextprotocol.io and https://aka.ms/mcp. I’ll continue to share how our customers and various industries are adopting MCP and the lessons we’re learning along the way. Stay tuned for more.Join Packt’s Accelerated Agentic AI Bootcamp this June and learn to design, build, and deploy autonomous agents using LangChain, AutoGen, and CrewAI. Hands-on training, expert guidance, and a portfolio-worthy project—delivered live, fast, and with purpose.This is it.35% off this Workshop - Limited Time OfferIf you’re in—move now.Code: AGENT35RESERVE YOUR SEAT NOW!📈LATEST DEVELOPMENTOpenAI Introduces Codex for Enhanced Code GenerationOpenAI has released Codex, a cloud-based AI agent for software engineering. Available in ChatGPT Pro, Enterprise, and Team, Codex (powered by codex-1) can write features, fix bugs, and answer codebase questions, operating in isolated environments. It learns from real-world tasks, producing human-like code and iteratively running tests. Developers can monitor progress, review changes with verifiable evidence, and guide Codex with AGENTS.md files.Microsoft Unveils Windows AI Foundry and Native MCP for Future AI AgentsMicrosoft is advancing its AI vision with native Model Context Protocol (MCP) in Windows and the Windows AI Foundry. This crucial groundwork, leveraging Anthropic's "USB-C of AI" protocol, aims to enable automated AI agents to seamlessly interact with apps, web services, and Windows functions. This initiative will empower features like natural language file searches and AI-powered system controls, reshaping how users engage with their devices.Google Launches AI Ultra: A VIP Pass to Advanced AIGoogle is launching Google AI Ultra, a new $249.99/month subscription (with an initial discount) offering the highest usage limits and access to its most capable AI models and premium features. Tailored for creative professionals, developers, and researchers, it includes Gemini with enhanced reasoning, Flow for cinematic video creation, Whisk for animated image generation, and advanced NotebookLM. Subscribers also get Gemini integration in Google apps (Gmail, Docs, Chrome), Project Mariner for multi-task management, YouTube Premium, and 30 TB storage.Apple to Open AI Models for DevelopersApple is reportedly preparing to allow third-party developers to build software using its AI models, aiming to boost new application creation. This move, expected to be unveiled at WWDC on June 9th, would let developers integrate Apple's underlying AI technology into their apps, starting with on-device models. This could help Apple compete in the AI landscape and enhance Apple Intelligence's appeal.GitHub Copilot Launches New AI Coding AgentGitHub Copilot now features an AI coding agent that tackles low-to-medium complexity tasks by simply assigning it issues. It operates in secure, customizable environments, pushing commits to draft pull requests with transparent session logs. This agent, enhanced by Model Context Protocol (MCP) and vision models, allows developers to offload routine work, ensuring security through human approval for pull requests and adhering to existing policies.📢 If your company is interested in reaching an audience of developers and, technical professionals, and decision makers, you may want toadvertise with us.If you have any comments or feedback, just reply back to this email.Thanks for reading and have a great day!That’s a wrap for this week’s edition of AI_Distilled 🧠⚙️We would love to know what you thought—your feedback helps us keep leveling up.👉 Drop your rating hereThanks for reading,The AI_Distilled Team(Curated by humans. Powered by curiosity.)*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0}#converted-body .list_block ol,#converted-body .list_block ul,.body [class~=x_list_block] ol,.body [class~=x_list_block] ul,u+.body .list_block ol,u+.body .list_block ul{padding-left:20px} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

Modern Portfolio Theory, Open-Source AI for Evolving Trading StrategiesEmbedded Protection, Built for ScaleWysh Life Benefit lets banks offer free life insurance through savings accounts, no forms, no opt-ins, no fees. Coverage grows with deposits and is paid directly to the account if the unexpected happens.Proven impact:3.8% growth in millennial deposits82% prefer it over higher APY4x ROI via upsell and affiliate revenueLive in under 45 days40,000+ accounts protectedBacked by Northwestern Mutual and Gen ReSmart, simple, and built for modern banking.Talk to Our Team TodaySponsoredSubscribe|Submit a tip|Advertise with us📬 Welcome to AlgoFinance #2 - Where Strategy Meets Systems in Modern TradingThis edition is all about leveling up your edge in algorithmic trading. From powerful APIs to open-source AI, and from classic chart patterns to modern portfolio optimization,we’ve curated the insights, tools, and strategies that matter most right now.Here’s what you don’t want to miss:🔗 Build Smarter Integrations: Master the OKX API for automated crypto trading, and explore plug-and-play solutions like Dhan Sandbox to test your algos with zero risk.⚙️ Choose Your Backtesting Arsenal: Compare PyAlgoTrade, Zipline, and Backtrader so you can pick the right framework to develop and fine-tune your strategies.🕯️ Trade the Reversal: Learn how the Bearish Engulfing Candle can be a key signal for short entries and risk-adjusted timing.🧠 Go Beyond Models: Discover how Modern Portfolio Theory and AI-powered strategy evolution can reshape how you think about diversification, alpha, and adaptability in a dynamic market.Whether you're coding your next system or optimizing your risk exposure,this edition is packed with actionable insights to help you trade smarter and build with confidence.🚀 Let’s get to it, your next trading breakthrough might be just one scroll away.Cheers,Merlyn ShelleyGrowth Lead, PacktMaster the Math Behind Machine Learning - Free Primer!Get a head start on our upcoming release, Mathematics of Machine Learning by Tivadar Danka, with this free downloadable primer.🔍 Inside:Core concepts: Linear Algebra, Calculus, ProbabilityClear explanations + hands-on Python examplesWritten by a PhD mathematician & ML educator📩 Enter your email to get Essential Math for Machine Learning delivered to your inbox within 24 hours.👉 Sign Up Now - Get Your Free Primer!🧠 Algorithmic Trading Strategies 📊🟦 Trailing Stops: What They Are & How to Use Them in Trading. Discover how trailing stops can transform your trading strategy by helping you manage risk and secure profits across markets like stocks, forex, cryptocurrencies, and commodities. This guide breaks down how trailing stops work, offers real-life examples, highlights common mistakes to avoid, and explores advanced techniques such as using multiple stops and adjusting for volatility. By automating your exits and reducing emotional decision-making, trailing stops allow you to trade more confidently and effectively, with practical insights drawn from case studies involving Apple and Bitcoin.🟦 Lessons From The Trading Floor: Building Trust In The CFD Market. In his reflection on the CFD trading industry, David Bily, founder of Moneta Markets, shares hard-earned lessons from his 15-year journey in forex andContract for Difference (CFD)markets. He emphasizes that trust is built through transparency, reliable platforms, proper regulation, and clear pricing win over flashy promises. Bily also advises both traders and brokers to keep technology purposeful rather than overwhelming, noting that simplicity often leads to better outcomes, especially for beginners. Lastly, he highlights the value of failure as a teacher, sharing how early missteps in rapid expansion taught him the importance of strategic planning over speed in building lasting global success.🟦 Introducing pwb-alphaevolve: An Open-Source AI for Evolving Trading Strategies: A groundbreaking open-source project, pwb-alphaevolve brings artificial intelligence into the heart of systematic trading by enabling autonomous evolution of trading strategies. Built on genetic algorithms and large language models, this tool lets an AI generate, mutate, and backtest strategies around the clock with minimal human intervention. With features like EVOLVE-BLOCK-coded templates, real-time backtesting, and a performance-driven evolution loop, traders and researchers gain a powerful assistant for discovering novel and optimized strategies. It’s an exciting step toward AI-assisted financial innovation, allowing users to test ideas faster, uncover unexpected patterns, and reshape how trading strategies are developed.🟦 Building Better Portfolios: Options, Models & Macro Risks. What happens when six brilliant minds with wildly different approaches weigh in on your portfolio? In this thought-provoking exploration, experts like Jim Shultz and Julia Spina share insights ranging from statistical edge cases and volatility detection to blockchain innovations and advanced modeling. Their collective wisdom highlights how a blend of quantitative rigor, technological tools, and human intuition can reshape how we assess and optimize portfolios. While AI and models offer powerful guidance, it’s the nuanced decisions made by real people that keep strategies grounded and adaptable in a complex market landscape.Machine Learning Summit 2025JULY 16–18 | LIVE (VIRTUAL)20+ ML Experts | 25+ Sessions | 3 Days of Practical Machine Learning and 35% OFFBOOK NOW AND SAVE 35%Use CodeEARLY35at checkoutDay 1: LLMs & Agentic AI From autonomous agents to agentic graph RAG and democratizing AI.Day 2: Applied AIReal-world use cases from tabular AI to time series GPTs and causal models.Day 3: GenAI in ProductionDeploy, monitor, and personalize GenAI with data-centric tools.Learn Live fromSebastian Raschka,Luca Massaron,Thomas Nield, and many more.35% OFF ends soon – this is the lowest price you’ll ever see.🤖 Machine Learning & AI in Trading 🧮🟦 OKX API Guide: How to Use OKX API for Trading & Integration. If you're looking to automate crypto trades or build sophisticated applications, the OKX API offers a comprehensive gateway into the exchange’s full capabilities. This in-depth guide walks through every essential step, from creating API keys and executing trades to real-time data streaming via WebSockets. With structured examples in Python and JavaScript, it demystifies authentication, strategy automation, and portfolio tracking. Developers and traders alike will appreciate tips on security, rate limits, error handling, and integration best practices. Whether you’re a beginner or a pro, this tutorial equips you to harness the OKX API for smarter, faster crypto operations.🟦 Integrating Day Trading Software with Brokers: In today’s fast-paced trading world, integrating your day trading software with a broker account is as essential as knowing the markets themselves. This guide explores everything you need to make that connection seamless, from generating API keys and selecting the right integration protocols to setting up automated trades and securing your systems. It explains how APIs like MetaTrader, Interactive Brokers, and REST interfaces power this connectivity, and offers best practices for testing connections, handling broker-specific features, and ensuring software compatibility. Whether you're fine-tuning your strategy or building a custom trading setup, this is your roadmap to smarter, safer trading integration.🟦 Dhan Sandbox: Kickstart Your Algo Trading Journey with Risk-Free Testing. Ready to experiment with algo trading without risking real money? Dhan Sandbox is your safe and seamless entry point. This fully simulated environment lets you test APIs, build trading logic, and simulate execution without needing a brokerage account or capital. With daily capital resets, static fill prices, and no live exchange exposure, it’s ideal for coders, traders, and fintech developers eager to build and refine strategies. Whether you're working with Python, TradingView, or OpenAlgo, Dhan Sandbox empowers you to innovate and iterate freely, no KYC, no funding, just pure experimentation.🟦 Metaconnector - The Future of Automated Trading: TradingView to MT5 Orders in 2025. Automated trading is redefining how modern traders operate, and MetaConnector is at the forefront of this shift. By linking TradingView alerts directly to MetaTrader 5 (MT5) orders, MetaConnector transforms analysis into real-time execution with speed and precision. This smart bridge uses webhooks to instantly convert signals into live trades, eliminating emotional delays and manual errors. Traders benefit from seamless automation, customizable risk controls, and multi-asset support, all operating 24/7 when paired with a VPS. As trading becomes increasingly competitive, MetaConnector equips you with a reliable edge, turning your TradingView strategies into automated MT5 executions with unmatched efficiency.🧑‍💻 Backtesting & Strategy Development 🔁🟦 Bearish Engulfing Candle: Understanding the Key Reversal Pattern & Trading Techniques. The bearish engulfing candle is a key pattern in technical analysis that signals a possible shift from an uptrend to a downtrend. It occurs when a small bullish candle is followed by a larger bearish candle that completely covers the previous candle’s body. This indicates that sellers have taken control, suggesting a potential reversal. Traders often use this pattern to identify entry points for short positions, especially when it appears after a strong upward move or near resistance levels. Confirming the pattern with volume, resistance levels, or indicators like RSI can improve its reliability and support better trading decisions.🟦 Best quantitative trading strategies using algorithmic models for high-frequency stock market analysis: Understandthe power of data-driven precision with the best quantitative trading strategies tailored for high-frequency stock market analysis. This comprehensive guide explores how algorithmic models are revolutionizing modern trading by using math, statistics, and machine learning to execute trades at lightning speed. Key strategies include latency arbitrage, order flow prediction, market making, and tick-level momentum detection, each designed to capitalize on micro-market movements. From developing and backtesting models with millisecond accuracy to managing risks and ensuring regulatory compliance, this approach empowers traders to compete in a market where milliseconds matter and algorithms drive performance.🟦 PyAlgoTrade vs Zipline vs Backtrader: Compare powerful Python tools with confidence by exploring how PyAlgoTrade, Zipline, and Backtrader stack up for algorithmic trading. This in-depth review breaks down each library’s strengths, from PyAlgoTrade’s simplicity and Zipline’s data integration to Backtrader’s robust multi-asset support and optimization capabilities. Traders can evaluate performance, flexibility, documentation, and live trading support to choose the right fit for their strategy complexity and asset scope. Whether you're a beginner looking for an easy start or an advanced user seeking customization and speed, this guide helps you align your algorithmic trading needs with the right Python library.🟦 How Algorithmic Traders Backtest Their Automated Strategies? Explore how algorithmic traders fine-tune their strategies through backtesting, a critical process that tests performance using historical data. This approach helps evaluate strategy effectiveness, identify potential flaws, and build confidence before live trading. Traders use tools like TradingView Pine Script, MetaTrader, and Python libraries such as Backtrader and Zipline for robust simulations. Effective backtesting requires clean data, multi-asset support, realistic cost assumptions, and avoiding pitfalls like overfitting or ignoring transaction costs. When executed properly, backtesting empowers traders to make informed, disciplined decisions based on data rather than emotion.📈 Portfolio Optimization & Risk Management 🏦🟦 Types of Risk in Portfolio Management & Ways to Manage: Take control of your financial future by learning how to balance risk and return in portfolio management. This guide unpacks the importance of understanding different types of investment risks, from market and credit to inflation and liquidity. Instead of avoiding risk, the key lies in managing it effectively through diversification, dynamic asset allocation, and disciplined strategies. Aequitas PMS exemplifies this approach with its research-driven, conviction-led investment philosophy focused on minimizing downside while maximizing long-term growth. With a transparent, low-churn framework and a commitment to protecting investor capital, Aequitas provides a resilient path for achieving stable, risk-optimized returns in unpredictable markets.🟦 5 Phases of Portfolio Management Explained for Smarter Investing: Strengthen your investment strategy by mastering the five essential phases of portfolio management. This structured process begins with security analysis, where investors evaluate assets for value and growth using financial metrics and tools like P/E ratios or discounted cash flow models. Next is portfolio analysis, which focuses on asset allocation, diversification, and balancing risk versus return. Portfolio selection follows, where the best mix of assets is chosen to meet financial goals. Over time, portfolio revision ensures the investments stay aligned with changing market conditions and personal objectives. Finally, portfolio evaluation measures performance through key metrics to refine future strategy. Together, these phases form a comprehensive framework for smart, goal-driven investing.🟦 Modern Portfolio Theory: What MPT Is and How Investors Use It. Build smarter portfolios by applying Modern Portfolio Theory (MPT), a foundational investment strategy that balances risk and return through diversification. Pioneered by Harry Markowitz, MPT focuses not on individual assets but on how they interact within a portfolio, using correlation and variance to reduce overall risk. By mixing high- and low-risk assets based on your risk tolerance, MPT helps investors optimize returns without taking on more risk than necessary. Whether through ETFs, mutual funds, or custom allocations, MPT empowers both individual and institutional investors to make data-driven decisions and construct portfolios that aim to sit on the efficient frontier, where risk is minimized and returns are maximized.🟦 9 Risk budgeting -MOSEK Portfolio Optimization Cookbook 1.6.0: Understand how risk budgeting enhances portfolio management by distributing risk, not just capital, across investments. Unlike traditional mean-variance optimization (MVO), which may overexpose portfolios to a few dominant assets, risk budgeting ensures each security contributes to overall risk in proportion to a predefined budget. This method uses marginal risk contributions to allocate exposure, resulting in portfolios that are more robust to estimation errors. By solving optimization problems, ranging from convex to mixed-integer formulations, investors can construct risk-balanced portfolios, including long-short strategies. Risk budgeting thus provides a mathematically sound way to achieve diversification and control volatility with precision.🟦 Financial Consulting in High-Value Portfolio Optimization: Advanced Strategies to Maximize Returns and Minimize Risks. Elevate your investment strategy by leveraging high-value portfolio optimization through expert financial consultancy. Managing substantial portfolios requires more than traditional investment approaches, it involves precision, advanced modeling, and constant adaptation. Financial advisors apply tools like Monte Carlo simulations, risk budgeting, and asset correlation analysis to fine-tune allocations, protect capital, and align with long-term goals. From tax planning and diversification to succession strategies and exclusive asset access, these services deliver a comprehensive framework for maximizing returns while minimizing risk. For high-net-worth individuals, a specialized consultancy is not just beneficial, it’s essential for navigating today’s complex and fast-moving global markets.*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0}#converted-body .list_block ol,#converted-body .list_block ul,.body [class~=x_list_block] ol,.body [class~=x_list_block] ul,u+.body .list_block ol,u+.body .list_block ul{padding-left:20px} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}