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Skeptical about AI? It’s normal (and healthy)

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Skeptical about AI? It's normal (and healthy)

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Less frightened. More fatigued. That’s where many of us reside with AI. Yet, I am in awe of AI. Despite the plethora and platitudes of AI promising to reshape industry, intellect and how we live, it’s vital to approach the noise and hope with a fresh excitement that embraces complexity. One that encourages argument and sustains a healthy dose of skepticism. Operating with a skeptical mindset is liberating, pragmatic, challenges convention and nourishes what seems to be a frequently missing sense of sanity, especially if you’re restless with endless assumptions and rumor.

We seem to be caught in a chasm or battle of ‘hurry up and wait’ as we monitor the realities and benefits of AI.  We know there’s an advertised glowing future and the market size of global AI is estimated to be more than $454 billion by the end of 2024, which is larger than the individual GDPs of 180 countries, including Finland, Portugal and New Zealand. 

Conversely, though, a recent study predicts that by the end of 2025, at least 30% of generative AI projects will be abandoned after the proof-of-concept stage, and in another report “by some estimates more than 80% of AI projects fail — twice the rate of IT projects that do not involve AI”. 

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Blossom or boom?

While skepticism and pessimism are often conflated descriptions, they are fundamentally different in approach.

Skepticism involves inquiry, questioning claims, a desire for evidence and is typically constructive laden with a critical focus. Pessimism tends to limit possibility, includes doubt (and maybe alarm), perhaps anticipating a negative outcome. It may be seen as an unproductive, unappealing and unmotivating state or behavior — although if you believe fear sells, well, it’s not going away.

Skepticism, rooted in philosophical inquiry, involves questioning the validity of claims and seeking evidence before accepting them as truth. The Greek word “skepsis” means investigation. For modern-day skeptics, a commitment to AI inquiry serves as an ideal, truth-seeking tool for evaluating risks and benefits, ensuring that innovation is safe, effective and, yes, responsible. 

We have a sound, historical understanding how critical inquiry has benefited society, despite some very shaky starts:

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  • Vaccinations faced heavy scrutiny and resistance due to safety and ethical issues, yet ongoing research led to vaccines that have saved millions of lives.
  • Credit cards led to concerns about privacy, fraud and the encouragement of irresponsible spending. The banking industry improved the experience broadly via user-driven testing, updated infrastructure and healthy competition.
  • Television was initially criticized for being a distraction and a potential cause of moral decline. Critics doubted its newsworthiness and educational value, seeing it as a luxury rather than a necessity. 
  • ATMs faced concerns including machines making errors or people’s distrust of technology controlling their money. 
  • Smartphones were doubtful given they lacked a keyboard, had limited features, battery life and more, yet were alleviated by interface and network improvements, government alliances and new forms of monetization.

Thankfully, we have evolving, modern protocols that — when used diligently (versus not at all) — provide a balanced approach that neither blindly accepts nor outright rejects AI utility. In addition to frameworks that aid upstream demand versus risk decision-making, we do have a proven set of tools to evaluate accuracy, bias, and ensure ethical use.  

To be less resistant, more discerning and perhaps a hopeful and happy skepsis, a sampling of these less visible tools include: 

Evaluation MethodWhat it does…ExamplesWhat it’s seeking as ‘truth’…
Hallucination detectionIdentifies factual inaccuracies in AI outputDetecting when an AI incorrectly states historical dates or scientific factsSeeks to ensure AI-generated content is factually accurate
Retrieval- augmented generation (RAG)Combining results from trained models with additional sources to include the most relevant informationAn AI assistant using current news articles to answer questions about recent eventsCurrent and contextually relevant information from multiple inputs
Precision, recall, F1 scoringMeasures the accuracy and completeness of AI outputsEvaluating a medical diagnosis AI’s ability to correctly identify diseasesBalance between accuracy, completeness and overall AI model performance
Cross-validationTests model performance on different subsets of dataTraining a sentiment analysis model on movie reviews and testing it on product reviewsSeeks to ensure the model performs consistently well across different datasets indicating reliability
Fairness evaluationChecks for bias in AI decisions across different groupsAssessing loan approval rates for various ethnic groups in a financial AIEquitable treatment and absence of discriminatory patterns and does not perpetuate biases
A/B testingRunning experiments to compare the performance of a new AI feature against an existing standardTesting an AI chatbot against human customer service representativesValidation, improvements or changes from compared performance metrics
Anomaly detection checksUsing statistical models or machine learning algorithms to spot deviations from expected patterns. Flagging unusual financial transactions in fraud detection systemsConsistency and adherence to expected standards, rubrics and/or protocols
Self-consistency checksEnsures AI responses are internally consistentChecking that an AI’s answers to related questions don’t contradict each otherLogical coherence and reliability; results are not erratic or random
Data augmentationExpands training datasets with modified versions of existing dataEnhancing speech recognition models with varied accents and speech patternsImproved model generalization and robustness
Prompt engineering methodsRefining prompts to get the best performance out of AI models like GPT Structuring questions in a way that yields the most accurate responsesOptimal communication between humans and AI
User experience testingAssesses how end-users interact with and perceive AI systemsTesting the usability of an AI-powered virtual assistantUser satisfaction and effective human-AI interaction

4 recommendations for staying constructive and skeptical when exploring AI solutions

As we continue to navigate this age of AI fear and excitement, embracing skepticism-based approaches will be key to ensuring that innovations serve the best interests of humanity. Here are four recommendations to stay mindful of and practice broadly.

  1. Demand transparency: Insist on clear technology explanations with referenceable users or customers. In addition to external vendors and industry/academic contacts, have the same level of expectation setting with internal teams beyond Legal and IT, such as procurement, HR and sales.
  2. Encourage people-first, grassroots participation: Many top-down initiatives fail as goals may exclude the impacts to colleagues and perhaps the broader community. Ask first: As non-hierarchical teammates, what is our approach to understand AI’s impact, versus immediately assigning a task force listing and ranking the top five use cases.
  3. Rigorously track (and embrace?) regulation, safety, ethics and privacy rulings: While the European Union is deploying its AI ACT, and states such as California attempt to initiate controversial AI regulation bills, regardless of your position, these regulations will impact your decisions. Regularly evaluate the ethical implications of these AI advancements prioritizing human and societal impacts over scale, profit and promotion.
  4. Validate performance claims: Request evidence and conduct independent testing when possible.  Ask about the evaluation methods listed above. This is especially true when working with new ‘AI-first’ companies and vendors.

Skepticism is nourishing.  We need methods to move beyond everyday chatter and commotion. Whether you’re in malnourished doubt, or discerning awe, this is not a zero sum competition. A cynic or pessimist’s gain does not lead to an equivalent loss in others’ optimism. I am in awe of AI. I believe it will help us win and our rules for success are grounded in humble judgment.

In a way, albeit with provocation, skepticism is a sexy vulnerability. It’s a discerning choice that should be in every employee manual to ensure new technologies are vetted responsibly without unattractive alarm. 

Marc Steven Ramos is chief learning officer at Cornerstone.

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Meta’s Movie Gen looks like a huge leap forward for AI video (but you can’t use it yet)

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Meta's Movie Gen looks like a huge leap forward for AI video (but you can't use it yet)

At this point, you probably either love the idea of making realistic videos with generative AI, or you think it’s a morally bankrupt endeavor that devalues artists and will usher in a disastrous era of deepfakes we’ll never escape from. It’s hard to find middle ground. Meta isn’t going to change minds with Movie Gen, its latest video creation AI model, but no matter what you think of AI media creation, it could end up being a significant milestone for the industry.

Movie Gen can produce realistic videos alongside music and sound effects at 16 fps or 24 fps at up to 1080p (upscaled from 768 by 768 pixels). It can also generative personalized videos if you upload a photo, and crucially, it appears to be easy to edit videos using simple text commands. Notably, it can also edit normal, non-AI videos with text. It’s easy to imagine how that could be useful for cleaning up something you’ve shot on your phone for Instagram. Movie Gen is just purely research at the moment —Meta won’t be releasing it to the public, so we have a bit of time to think about what it all means.

The company describes Movie Gen as its “third wave” of generative AI research, following its initial media creation tools like Make-A-Scene, as well as more recent offerings using its Llama AI model. It’s powered by a 30 billion parameter transformer model that can make 16 second-long 16 fps videos, or 10-second long 24 fps footage. It also has a 13 billion parameter audio model that can make 45 seconds of 48kHz of content like “ambient sound, sound effects (Foley), and instrumental background music” synchronized to video. There’s no synchronized voice support yet “due to our design choices,” the Movie Gen team wrote in their research paper.

Meta Movie Gen

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Meta says Movie Gen was initially trained on “a combination of licensed and publicly available datasets,” including around 100 million videos, a billion images and a million hours of audio. The company’s language is a bit fuzzy when it comes to sourcing — Meta has already admitted to training its AI models on data from every Australian user’s account, it’s even less clear what the company is using outside of its own products.

As for the actual videos, Movie Gen certainly looks impressive at first glance. Meta says that in its own A/B testing, people have generally preferred its results compared to OpenAI’s Sora and Runway’s Gen3 model. Movie Gen’s AI humans look surprisingly realistic, without many of the gross telltale signs of AI video (disturbing eyes and fingers, in particular).

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Meta Movie Gen

Meta

“While there are many exciting use cases for these foundation models, it’s important to note that generative AI isn’t a replacement for the work of artists and animators,” the Movie Gen team wrote in a blog post. “We’re sharing this research because we believe in the power of this technology to help people express themselves in new ways and to provide opportunities to people who might not otherwise have them.”

It’s still unclear what mainstream users will do with generative AI video, though. Are we going to fill our feeds with AI video, instead of taking our own photos and videos? Or will Movie Gen be deconstructed into individual tools that can help sharpen our own content? We can already easily remove objects from the backgrounds of photos on smartphones and computers, more sophisticated AI video editing seems like the next logical step.

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Racking up major purchase conversion rates with mobile game web shops

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Racking up major purchase conversion rates with mobile game web shops

Presented by Xsolla


In a world of ever-declining revenue margins for game developers, direct-to-consumer is becoming essential. Cost-effective services, platforms and tools to build web shops are thick on the ground, and game companies of any size can afford to get set up, sell and rack up some astonishing numbers, says Artem Liubutov, head of monetization at Xsolla.

Across the 400 web shops Xsolla has launched, the minimum increase in game revenue has been in the range of 10% to 16% and the conversion rate, from logging in to the web shop to purchase, ranges between 40% and 60%, Liubutov says. And now 40 out of the top 100 grossing games in the world are working with them, including Tilting Point, Godspeed Games, Hyper Hyppo and Kefir.

“If a game has done things properly, if they transfer paying players and avoid spending marketing money on transferring non-payers, these numbers are totally doable,” he explains. “Big publishers, mid-size publishers, even relatively small mobile games can achieve that without spending a lot of money on marketing. You can do it very smartly with web shops.”

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Adding player value

A web shop is really all about the value-add. It should be a place where players can find unique items that enhance the playing experience and offers valuable items. Thoughtful, high-value offers attract the most valuable players — the big spenders who enthusiastically spend beyond the $99.99 price point that traditional platforms are limited to.

“Web shops are perfect for whales and super-whales,” Liubutov says. “They’re willing to spend much more in exchange for additional value, which not only leads to increased average purchases, but also the number of repeat purchases, and as a result, retention and LTV, since they want to use what they bought.”

Web shops are also capable of re-anchoring players to a new price point — many developers have seen their price point go sky-high. As the new purchasing experience is entirely familiar to players, it increases their comfort in shelling out rather than to a shill inside their game.

So when a high price point is combined with a commensurate amount of perceived value, players can actually shift from one segment to another. For example, from dolphins to whales, from whales to super-whales.

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“For some games, especially for core genres like 4X strategy and RPG games, these very expensive packages can bring more than 50 percent of all revenue in the game,” he says. “That’s something we didn’t expect three years ago, but now we’ve seen this happen more and more.”

Getting started for success

Setting up a web shop is easier than ever. Xsolla just launched Web Shop 2.0, as well as their Instant Web Shop, which can get you up and running in 24 hours. But doing it right demands some time and care right out of the gate. The analysis stage is particularly important, Liubutov says, and he identifies three major areas to dig into.

1. Analysis of already launched web shops, especially for games in similar genres. Pay attention to what they sell, their price tiers and what kind of promotions and live ops they’re using.

2. Analysis of the existing target audience and segmenting players — especially paying players, since they’re obviously your bigger fans and best customers. Break down which in-game activities have the most impact on every segment, and whether each segment responds better to discounts or to added value.

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3. Analysis of items and offers in the game — determine which generate more revenue, and how each segment reacts to each price point.

And remember, there’s no limit to the price point in a web shop, and price experiments are easy to stage. A $10K package might sell, if there are enough dedicated players — and developers are often surprised to find that they have players who can and will spend far more than they thought.

“With web shops, the goal is to change behavior, to form a new spending habit — basically to make a paradigm shift,” Liubutov explains. “The new normal should be that mobile is where I play and the web is where I pay.” 

The five golden rules of building a webshop

While Xsolla has partnered with developers of every size to build and launch successful web shops, they’ve arrived at five principles, or golden rules, for success.

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Rule #1

Treat the web shop as an extension of the game. To form a habit, everything should be easy. For example, if the web shop’s UI is different from the game’s UI, a player will face a learning curve when trying to figure out how to use the shop, where to go and how to pay.

“In the first nanosecond when players see the web shop, you want it to feel completely familiar, with the same colors, same buttons, same flow, same logic, same types of offers, same events happening, which makes it much easier to start purchasing,” Liubutov says. “It may sound pretty obvious, but almost everyone that we’ve seen, including the biggest publishers in the world, they keep making this mistake. It happens when two very separate teams operate on in-game purchases and on the web shops, without communicating with each other.”

Rule #2

Continuous communication is key. It’s an endless cycle of telling players about the existence of the web shop, and then continuously reminding them that it exists. Yes, they’re endless tasks, but they’re crucial for success. Build a direct communication tool immediately, if you don’t have one already, whether it’s Discord, Facebook or a forum.

Rule #3

Friction is your biggest enemy, and it leads directly to churn. Authentication is a big sticking point, as is laboriously entering payment methods, and making it difficult to calculate the difference in value between in-game offers and web offers.

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Rule #4

Value is king in web shops. Liubutov recommends a 10% increase in value or a 10% discount to start. The benefit should be much higher than the transactional cost of a new game experience.

Rule #5

Leverage the web shop’s live ops power. It’s possible to just sell evergreen virtual currency packages and see a 10% increase in revenue. But by leveraging all the live ops capabilities — by segmenting players and doing personalized offers, loyalty programs, targeted bundles and first-time offers — the increase is staggering, Liubutov says. And the best way to do this is by having the in-game live ops team work with the web shop live operations.

“If you follow those five rules, if you pay attention to your metrics and think about value and push live ops, the increase in revenue can be very substantial. The pure ROI on doing a web shop is very high,” Liubutov says. “We know billion-dollar games that have now fully embraced a web shop strategy. It’s a number-one priority for these games, because of the value they’ve received in the last year or two working with us or doing this on their own.”


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Server Room Setup | Tech tricks and tips Patch panel #shorts #rntechtips

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What Does Server Room Mean? A server room is a room used to store, power and operate computer servers and their associated components. This room is part of a data center, which typical houses several physical servers lined up together in different form factors, such as rack mounted, or in tower or blade enclosures.

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My favorite thing about the Samsung Galaxy Z Flip 6 isn’t that it folds

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Samsung’s mid-year Galaxy Unpacked launch for 2024 was a bit dull. The Galaxy Watch range didn’t see many improvements bar the introduction of the Ultra (which is really only intended for the most diehard fitness heads), and time was mostly devoted to the show stopping Galaxy Ring, an entirely new product category for the smartphone maker (one that I’m excited for in Australia, where it is still yet to launch). Combined with an extremely lukewarm year for the sixth generation Samsung foldables, the Galaxy Z Flip 6 arguably received the least love of all the new gadgets – but I’ve come to appreciate the phone for what it is beyond the obvious gimmick.

The Galaxy Z Flip 6 has existed in a weird space among Samsung’s premium phone lineup for some time now. Vertically foldable akin to trendsetting phones of the 2000s, the Z Flip’s only real drawcard is in the name – it’s fashion before function. The Galaxy Z Fold 6 makes a much better case for its existence, acting as a tablet-phone hybrid, albeit at a high price point.

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NYT Crossword: answers for Saturday, October 5

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NYT Crossword: answers for Monday, September 23


The New York Times crossword puzzle can be tough! If you’re stuck, we’re here to help with a list of today’s clues and answers.

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