Category: Rants

  • The Rot of Short-Termism in VC

    The Rot of Short-Termism in VC

    Venture capital is a seriously long-term game, with investments taking somewhere between 8 and 16 years to return liquidity.

    The distance to that horizon creates a lot of eccentricity.

    For example, VC does not reward following patterns or navigating market movements, neither of which is relevant to decade-long cycles. Consensus of pretty much any kind is toxic, as the more people agree with something the less profitable it becomes. Investment experience is like comfortable entropy, slowly eating-away at your ability to remain objective.

    In a sense, success itself is antimemetic: the better the outcome of an investment, the more likely you are to try and repeat it through pattern matching — destroying the calibration which allowed you to find it in the first place.

    Can you imagine how maddening that is?

    This is why the best GPs are oddballs. They live with the paradox that being a ‘good investor’ is a process of constant discovery, and the more lost you feel the better you are probably doing.

    It takes a certain madness to do well, and that is not something you can pick up on the job. You cannot be taught how to think in a contrarian manner. Nobody can give you the confidence required to wait a decade to see if you have good judgement. You have it, or you don’t.

    This is why great VCs earn a lot of respect. The role they play in financing entrepreneurial dreams is critical. From the semiconductor origins of Silicon Valley to SpaceX and our future on other planets, someone had to be there to write the check.

    If the incentives were well aligned, that’s where this story would end — as a fan-letter to weirdos. VC would remain a cottage industry investing in wacky stuff, offering strong returns for LPs.

    Unfortunately, that is not the case.

    Over the past decade we’ve seen the emergence of a new type of VC: one who moves between trends with the swagger of a heat-seeking missile, investing as if their money might go bad. This behavior is contrary to pretty much everything that we know about venture capital, and yet the trend has only accelerated.

    To understand why, we have to look at VC compensation:

    The ‘2 and 20’ structure of VC compensation is pretty well understood and has remained unchanged for a long time: You get 2% of the fund per year in ‘management fees’ to pay your bills and support portfolio companies, and 20% of ‘carried interest’ as a share in any profits made.1

    For people passionate about the outliers, carried interest is the hook. Secure enough big wins and you can make a vast amount of money, in contrast to management fees which aren’t exactly lucrative for a small fund. It’s also nice that carried interest aligns success of the firm with success of the founders.

    However, as capital flooded into private markets over the last couple of decades, and exits took longer to materialise, some cunning individuals recognised an opportunity: the 2% is guaranteed, independent of performance, and it is possible to ‘hack’ venture to maximise that income.

    You can do things the old fashioned way, raising (for example) two $100,000,000 funds in a ten year period, with the implied annual income of $4,000,000. Alternatively, you can squeeze three funds into that period, at double the size, and scale your income to a mighty $12,000,000. All without really needing to worry about underlying performance.

    To build that second scenario, you need to do three things:

    • Invest in the most overheated, capital-intensive industries, which allow you to justify raising and deploying larger funds ever more quickly. These industries are also an easy-sell for LPs, who want something to talk about at dinner parties.
    • Systematically undermine the understanding of valuation by promoting crude and illogical practices, and calling people nerds if they say things like “free cash flow”. Venture is a craft, not a science — which basically gives you carte blanche, right?
    • Pour capital into brand and status building for your firm, which LPs love. Celebrities, political figures, impressive offices, big events… Anything that shows them you’re a serious institution (with the perks that entails) and not some garage-band firm.

    Instead of looking 8 to 16 years in the future with your portfolio, you want to focus on the next 2 to 3 years in order to align with your fundraising cycles. You want companies that are likely to grow in value rapidly in the near future, so hype and consensus are powerful allies.

    The aim is to invest in a company at Seed and propel it to a Series A within 2 years at a 4-5x markup, which — if you can repeat it often enough — will look great to LPs. If they ask about DPI just talk about how the IPO markets should open next quarter next year.2

    It doesn’t even matter if you don’t think your portfolio companies are attractive investment with that markup, as there’s no obligation to participate. You have the growth on your books to help you raise the next fund, and some compliant downstream bag-holders, that’s all that matters.

    You can even build this strategy into how you price deals. Rather than try to objectively value the business, just tell founders to think about what a reasonable Series A price would look like for them, and then divide it by 3 for the Seed. That way, you’ve got the expectation of at least a 3x markup already built-in to the investment!

    You want to make sure the heat persists, to ensure prices at later stages remain frothy and your markups get better and better. So consider a bit of thought leadership to keep interest on your chosen sector. As long as LPs believe the hype, and keep investing in other funds on that theme, capital will keep piling in. Amplify that market momentum as much as possible. Volatility is your friend, and over time it can even help you wash out smaller managers that offer an unfavourable comparison on performance.

    Obviously the actual investment returns from this strategy are likely to be terrible, unless you’ve somehow timed another ZIRP/2021 exit phenomenon and can unload all of your crap on the public markets just before the music stops. It doesn’t really matter, because the median return in VC is so poor that you might just luck your way into top quartile anyway. Keep the paper marks strong, keep bullshitting LPs about the market conditions and the insane potential of whatever it is you are investing in, and you can probably keep buying back in with a new fund.

    It’s going to be toxic to founders, as they watch huge piles of capital being incinerated chasing hype instead of genuine innovation.

    It’s going to be toxic to innovation, as founders increasingly choose to pursue ideas that they think VCs will back, rather than real passion projects.

    It’s going to be toxic to VCs, as good practices around markups, pricing and portfolio management are ditched in favour of capital velocity and short-term incentives. It’s already frighteningly clear how much basic investing knowledge washed out of VC during ZIRP.

    It’s going to be toxic to LPs as already pretty shitty performance metrics for venture capital get even worse.

    1. The management fee is often frontloaded and scales back after the investment period. The 20% carried interest may also have a hurdle rate (e.g. 8%) which guarantees some return on investment for LPs before they split profits with the VC. [↩]
    2. It might not matter though, as many institutional LP allocators collect their bonuses on markups, so their incentives are totally aligned with yours. They’ll probably have moved on to a new job in a few years anyway. [↩]
  • Deus Ex Machina

    Deus Ex Machina

    The success of AI is existential for venture capital

    Imagine entering VC in 2020, full of enthusiasm about a the unstoppable wave of technology. Your peers are impressed; it’s a prestigious industry that is perceived as commanding a lot of power through capital.

    You have to put aside your personal thesis in favour of the firm’s strategy on crypto, micromobility, rapid delivery, creator economy, and web3. Each of those sectors are benefitting from venture capital enthusiasm and weaponised capital, driving prices through the roof. It’s an exciting time, though you’re not feeling as involved as you would like to be.

    In fact, you’d quite like to make the case for investment in other industries; overlooked opportunities which offer larger ownership stakes and cleaner cap tables. It’s difficult to justify the change of strategy when the biggest markups are all coming from a few hot sectors, so you avoid the friction.

    Andreessen and Sequoia can’t be wrong, right?

    Capital is flowing into the asset class from LPs at an unprecedented rate. Rather than pressure to justify and properly diligence investments, you are pressed to ensure capital is deployed and opportunities aren’t missed. Access to hot deals and co-investment with the tier-1 firms is how you stay relevant to LPs. Success is now largely dependent on your relationships across the industry.

    It creeps up on you that your colleagues have stopped talking about exits. TVPI looks phenomenal. There’s no rush for any portfolio to go public. Now the conversation is about pricing and the appetite of downstream investors. Beyond that, it’s someone else’s problem.

    For the first time, your spidey-senses start to tingle.

    Early in 2022, concern ripples across the industry. Worries of recession, interest rates on the rise, and a weak public market that has lost interest in recent VC-backed IPOs. In simpler times, you would have papered over the cracks by highlighting fund resilience. Now, the idea fills you with dread. None of your portcos are growing much and auditors are on your tail to correct markups.

    With surprising speed, the tables turn. An era of unprecedented growth and optimism comes to an end. Y Combinator writes the eulogy with an open letter to their portfolio companies. Venture-backed hypergrowth is shelved in favour of finding a path to profitability. The red-hot sectors which had promised game-changing returns are quietly scrubbed from websites and bios.

    By Mid-2023, venture capital feels like a fever-dream. Many of the most exciting investments from 2020 and 2021 have imploded or recapitalised. Layoffs are the norm, even for many VC firms. Nobody in the arena wants to talk about why.

    Fortunately, nobody has to dwell on the cause of the downturn for too long: exciting new tech from companies like OpenAI and Midjourney provides the perfect source of distraction. A whole new gold rush to sell to LPs.

    The incredible possibilities offered by powerful, accessible AI models will spawn companies with growth potential not seen since the early years of Google and Amazon. It promises to easily turn-around a few years of poor performance for the venture asset class.

    Of course, there are nay-sayers. Not the doomers who speak of an AI-driven apocalypse, at least they buy into the incredible scope of the technology. They are believers. The real problem are the cynics.

    The cynic’s claim is that today’s “AI” is just an evolution of decades-long work on machine learning, neural networks and natural language processing. Yes, the hardware is a lot better, processing at scale is much easier, but fundamentally not a huge amount has changed. Models will be commoditised and commercial applications will favour incumbents who have data and distribution. It’s not the generational game-changer that venture capitalists claim.

    Those who believe the hype (or those whose career depends on it) preach the gospel of salvation for an entire generation of managers. The narrative battleground is shifted to the conflict between these two groups, the doomers and the boomers, away from the cynics who offer nothing but grim reality.

    Evangelism reaches new heights. Marc Andreessen who led the charge on the 2011 – 2022 bull run with his essay, “Why Software Is Eating the World“, proclaims even greater optimism with the publication of “Why AI Will Save the World“.

    It gnaws at you. Do you really believe? Do the numbers make sense, or is venture capital back at its usual bullshit? Is it your responsibility to just blindly support this as an insider?

    Worse, what if this fails too? The consequences for the venture asset class are difficult to contemplate.

    At some point, you are sure the music is going to stop.

    Until then, the only path you can see is to continue following your peers. As long as you are all doing the same thing, no failure can be pinned on you.

    …Right?

    Each day you scramble to find the hottest AI deals in your network and secure allocation. You keep making the same promises and assurances.

    You lean into the identity, blend into the herd. Any sense of irony in wearing the uniform disappears. You begin to believe.

  • “Why don’t VCs set marks with 409a valautions?”

    “Why don’t VCs set marks with 409a valautions?”

    This is a question I saw on Reddit’s often-comical /r/venturecapital, which I thought was interesting enough to write out a decent response to. It hits at the root of a few major problems in the asset class which are always worth addressing.

    A 409A valuation, named after Section 409A of the United States Internal Revenue Code (IRC), refers to the process of determining the fair market value of a privately held company’s common stock. It is often conducted to comply with the tax rules governing non-qualified deferred compensation plans, such as stock options, stock appreciation rights (SARs), and other equity-based compensation arrangements.

    A lovely summary from ChatGPT

    First thing’s first: Generally speaking, VCs don’t care about valuation, and especially not ‘fair value’.

    …and that’s quite reasonable. VCs have their own investment strategy, their own approach to calculating risk vs potential, and if it works for them (and their LPs) then great. More power to them.

    What’s important here is that while we often use the word valuation in reference to deal terms and portfolio performance, what we really should say 99% of the time is price.

    In venture capital, price factors in a number of things, including the advantages of preferred stock over common stock, but most significantly it is geared at reflecting what the market would be likely to pay for that startup at the time. This is why VCs focus so much on comparable deals when pricing rounds, even if it ends up being a bit circular, with everyone copying everyone elses homework.1

    So that is the status quo. But why are VCs interested in preferred stock in the first place?

    Venture capital is all about power law, right? The idea is to invest in many startups, expect to lose money on 80%, and make a varying amount of money back from the remaining 20%.

    So why do they care so much about downside protection, rather than maximising that upside?

    When you add a liquidation preference to a deal, the implied value of the equity increases, meaning you get a smaller % for your capital. Lower returns at exit. That kind of trade-off flies in the face of power law, so why is it of interest?

    There’s a clue in this great article from William Rice:

    Liquidation preferences insulate VC firms from losses, so they can delay markdowns until after they raise another fund. VC returns follow a J-curve, therefore losses come much earlier than returns. Liquidation preferences can serve as valid reasons to not mark-down investments as companies begin to miss milestones or don’t receive an exciting Series A valuation bump.

    William Rice, “Slugging Percentage vs. Batting Average: How Loss Aversion Hurts Seed Investors”

    Liquidation preferences are mostly an irratational response from loss-averse VCs, some of whom may be trying to shield themselves against reporting poor performance to LPs. Maybe that’s overly cynical; I’m all ears if anyone has a better explanation.

    The core assertion here is that in a more rational and healthy market, liquidation preferences probably wouldn’t exist and VCs would just buy common stock.

    An industry with few standards

    Now that we have some understanding of how equity is priced and why preferences exist, let’s return to the original proposition: that VC investments could be marked up or down based on 409a valuations.

    In some cases, VCs do set marks with 409a valuations, but not all. Unfortunately – as with much of VC – there are no real standards.2

    Some VCs will only set marks based on fundraising activity, some will also consider 409a updates, some will factor new SAFE caps. Some will ignore downrounds, some won’t.

    The way VCs price rounds is subjective and non-standardised, and therefore way they track the value of those investments is also subjective and non-standardised.

    It might be going too far to say that this was all designed to obscure performance and protect charlatans, but this is probably how I would design VC if that was my intention.

    Performance > relationships

    Putting aside deal pricing for now: a VC firm could use any framework that provides a systematic read on fair value, such as this one from Equidam, and apply that to tracking portfolio company performance.

    This would represent a huge shift in how VCs operate, and how they manage relationships with LPs. It’s also something that I’ve written about at some length before.

    The horizon for useful feedback could be annual (or even quarterly) rather than 5-10 years.

    LPs could hold fund managers accountable for performance, and we may see that many household names (which attrract the lion’s share of capital and startup attention) are actually dramatically underperforming. They could more confidently back emerging managers, who could provide more meaningful metrics of success.

    VCs would be able to follow portco growth more precisely and learn much more quickly about what works and what doesn’t. Good managers would be able to fundraise much more easily.

    Crucially, it would make VC an industry based on performance rather than relationships and hype chasing as it is today. It would make VC better at backing innovation, which is what the whole asset class was built around.

    Startups are volatile, but capital should be stable

    Finally, if VCs were also to price deals based at least partially on fair value, we’d avoid momentum-driven valuation rollercoasters like we’ve seen in the last two years. Much less risk of valuation bubbles and crashes, more stability for LPs and VC funds, more consistent access to capital for founders, and – again – an asset class that could better serve innovation.3

    A more objective and independent perspective on startup potential, better suited to investment in the innovative outliers that venture capital was created to support.

    I’ve spoken to a number of people – LPs, VCs and founders – about this topic. There’s a near universal acceptance that a standard for private company valuation would be of huge benefit to the whole venture ecosystem.

    Unfortunately, none of them are particularly incentivised to make a stand on it.

    Some may benefit from the status quo, and the rest are keen to maintain their relationships by not making waves.

    1. Thus bubbles, etc… more on that later. [↩]
    2. If anyone has any data on this, I’d love to see it. [↩]
    3. There are also huge second-order effects, like how it would make venture capital fairer by removing more of the bias found in less structured approaches to valuation – but that’s for another post. [↩]
  • Generative AI and the Games Industry

    Generative AI and the Games Industry

    This post looks at applications of generative AI in the context of the games industry, but much of the same logic can be applied elsewhere.

    Adapting to technological evolution

    With every new technology revolution – web3 most recently, and now AI – there follows a large herd of true believers. It can do all things, solve all ills, and life will never again be the same again. Enamoured by possibility, they follow with a true sense of opportunity.

    Loudest amongst this herd (and most critical of nay-sayers) are the wolves in sheeps’ clothing. The rent-seeking charlatans.

    This was explicit in the get-rich-quick era of web3, and much of the same problem has transferred over the AI as techno-pilgrims flee one sinking ship to pile into another.

    Secondly, on the other side of the coin, are the cynics. People who were raised on 56k modems and bulletin boards, who feel a deep discomfort as technology moves beyond their grasp. They felt like the rational resistance to web3, and so have little hesitation about weighing in on AI.

    We have to be conscious of both groups, and our own place on that spectrum.

    Why the games industry?

    There are three main reasons I’m keen to address the games industry as the case-study for this post:

    1. As with web3, AI is being shoved down people’s throats without due concern for why.
    2. It is largely focused on a young audience who are absent from these conversations.
    3. It connects with my personal experience in the games industry.

    If you want to read about the potential use cases for AI in banking, you’ll find a thousand thought-leader think-pieces. It was well-covered ground without much original thought even before ChatGPT came along.

    If you want to talk about the potential use cases of AI in the games industry, you’ll find some ex-crypto VCs and technologists trying desperately to pivot their brief experience. Insubstantial waffle.

    Perfection is the enemy of good

    Dealing with the more exciteable technophiles, you’ll probably notice they don’t show a lot of interest in the complex applications. Their interest is in the most extreme examples of movies, games or books being entirely generated by AI (or entirely decentralized, yada yada).

    Their point is simple: if AI can do these things crudely today, then tomorrow it will be able to do them well – and at that point we’ll be forced to embrace the bold new future. Right?

    This fallacy can be observed in every parent watching their child smear paint on paper for the first time: something inside them says ‘they could be a great artist’. It’s true: the ability to manifest art can be that simple, and the child has huge potential for improvement… Yet it’s still not going to happen for all but a miniscule few.

    In both cases, the AI model and the child, there cannot merely be push, there must also be pull. There must be a need being met. An appetite being satisfied. And 99% of the time, there isn’t. Once the novelty has worn off, nobody has any interest in watching an AI-generated movie, reading an AI-generated novel, playing an AI-generated game, or looking at your child’s paintings. There just isn’t a call for it.

    Instead of putting AI on the pedestal of a godlike creator, we should look at where it can be a tool to solve a problem.

    Merchants of fun

    You can get side-tracked in talking about experiences, socailising, adventuring, exploration, curiosity, challenge, status… Ultimately, games are vehicles for fun. That’s bedrock.

    Is an AI-generated game likely to be more fun than the alternative? No, of course not, and if you suspect otherwise then you’ve not spent enough time with the wonderful and wacky people who make games. They are true creatives.1

    Any application of generative AI to the games industry must have either enhance fun, or enhance the developers ability to deliver it.

    Exploration

    If you look at games like Minecraft or 7 Days to Die where you can explore a proceedurally generated world, it’s easy to see how generative AI might be able to supercharge that environment building.

    It’s worth considering, though, that this is a specific approach for a specific type of game. As good as these engines have gotten, most of the time games will require a more ‘designed’ world, with geography or features which play into gameplay mechanics, story elements or IP. Generative AI may offer tools to make this more efficient (as many proceedural tools already do), but is unlikely to replace it entirely.

    Socialization

    Imagine walking around a Skyrim or Cyberpunk style sandbox-world, full of NPC characters with their own unique look, voice, and personality. Each able to hold a conversation with you, flavoured with their own specific personality and knowledge. Not merely giving canned responses to pre-defined prompts, but able to interact fluidly with you and amongst themselves.

    Again, this is unlikely to ever be all a game needs. Stories still require specifcally designed characters with particular roles which need to be shaped by the intention of writers and a design team, but it is still a tremendous opportunity to solve the social component of virtual worlds.

    These are two quickly-sketched examples of how generative AI could enable a leap forward in the experience provided by games devleopers – and I am sure there are many more to be found.2

    Tapping into the market

    I wanted to do this in a more subtle manner, but it’s just more practical to break down Andrew Chen’s Twitter thread:

    Games can take 3+ years to build, and technology adoption happens at specific windows of time

    If your generative AI tool is a plugin (for the Unreal Engine, for example) then a studio can pick it up at any time and add it to their development stack.3

    You shouldn’t be limited to thinking in terms of ideas that are ‘disruptive’ to how games are made, and indeed most of the opportunity may be in ideas which are complimentary.

    indie games make little $. There’s only a few scaled players, who will always push on pricing

    If you were going to target indie developers it would have to be with a very specific value proposition and business model (e.g. Unity in 2004). There’s no reason to worry about this otherwise; there are enough larger studios.

    the games ecosystem is insular, with its own conferences, luminaries, and networks / networking” in the games industry often involves, well, gaming. Are you good at Valorant? 🙂

    Can you tell me an industry which doesn’t have its own conferences, luminaries and networks?

    The games industry is not insular, and it is comical to characterize it as a bunch of nerds playing games together. It’s a wonderfully open, social and diverse community.4

    a large % of game cos have artists and creative people. Many are threatened by, and oppose, AI tech

    I don’t know of anyone in the games industry, artist or designer, who isn’t starry-eyed at the possibilities of what AI can enable.

    They are also familiar enough with how games work to recognise that human input is always going to be required to shape and polish the human experience which emerges on the other side.

    you need to generate editable, riggable, high-quality art assets. Right now assets are idiosyncratic and hard to edit

    Generative AI has not yet proven that it can generate useable assets, never mind well-optimised thematic assets. That problem can probably be solved, but to what end?

    Will a world created by a generative AI ever truly feel interesting, coherent, beautiful? Maybe there are better things for it to do?

    large publishers often provide tech to their internal studios. They’ll partner to learn about AI, but will try to build in-house. Is your tech defensible?

    That might have been the case 15 years ago, but the vast improvement in game engines and tools has meant that developers are much more likely to build on existing platforms.

    If a publisher believes that a tool would make development cheaper and faster then they’ll support it without blinking.

    large gaming cos care a lot about their models and data not being shared across the industry. How do you guarantee that? / they also care that their models are trained on data that’s safe from a copyright perspective. There’s lots of hoops to jump through

    Stretching a bit here, but: You train your tools on an open set of data to the point where they are useable, and allow developers to provide additional training based on data from their own IP. In that scenario there is no reason for crossover between studios.

    It’s unlikely that training from one game would ever be useful to the application of the AI in another. It is probably more likely to produce undesirable results.

    Conclusion

    Some years ago an associate of mine went to interview for a job at a games company in Seattle. The interviewer had previously been the lead designer on Starcraft, and naturally expected the candidate to play a match against him while fielding questions about the role.

    The games industry is full of these amusing anecdotes of quirky behavior, and there is a pronounced culture associated with that. However, it is condescending to think that culture stands in the way of progress, or that games studios can’t engage with business and technology partners in a perfectly competent manner.

    If you make a useful tool which solves a problem for the games industry, you will be able to access the right people to make a sale. I’d go so far as to say it’s probably easier and faster moving than many other industries.

    If that is your aim, make sure you are spending enough time talking to games developers, learning about how games are made, understanding the player mentality, and the problems that you might be able to address. As always, finding product:market fit can require a lot of learning and iteration.

    Most of all, ignore the false prophets who were reading from the web3 gospel just a few months ago. They will just ride this trend until something else comes along.

    1. Yes, throughout this article I am drawing a deliberate and passive-aggresive distinction between ‘creating’ and ‘generating’. [↩]
    2. It bothers me that I covered Explorers and Socializers, but didn’t have the time to identify anything for Achievers and Killers. [↩]
    3. And in most mid-large studios there are usually multiple teams running in parallel focused on different projects at different stages of development. [↩]
    4. The irony of a venture capitalist calling the games industry ‘insular’ is not lost on me. [↩]
  • Metaverse – Reinventing the wheel

    Metaverse – Reinventing the wheel

    Earlier this week, web3 Studios released their ‘Digital Identities Report‘, sharing a variety of opinions and predictions on the future of identity and social interaction in a ‘metaverse’ environment.

    There is more than fifteen years worth of fascinating sociological research on virtual worlds and digital identity. You would not know that from reading this report.

    It simultaneously presents web3 worlds as an entirely new concept that is being shaped by a new generation of ‘web3 thinkers’, while also positioning Roblox as an example of a metaverse.1

    I’ve written about this before. Specifically in regard to web3 enthusiasts ignoring the incredible groundwork down in science fiction and games, and more recently on how metaverses are fundamentally a non-technical social proposition.

    Mostly those arguments have addressed the general web3 discourse on Twitter, wishing it was better informed about the existing groundwork in this field.

    It’s a deeper issue when companies (selling web3 products) collaborate with web3 influencers (mostly NFT shills) to produce a report that is essentially a sales catalogue – but frame it as some insightful look at the social aspects of virtual worlds.

    We’re all supposed to rub our chins, and ponder this brave new world of identity in a digital environment. Once we buy one of their avatars, of course.

    So, here (and in the corresponding Twitter thread) I wanted to share a few genuinely good papers on the sociology of virtual world and digital identity:

    If you are genuinely interested in building the future of social interaction online, there is an absolute wealth of information available to you. It is well covered ground – thanks to genuine experts, who often spent years immersed in virtual worlds as a part of their research.

    Stretch your legs, take a wander outside of the web3 bubble.

    1. Roblox is an online game released in 2006, enjoyed by an audience that is mostly under 12 years old. Did you know that Gucci have a ‘metaverse’ installation there? [↩]