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How Niantic evolved Pokémon GO for the year no one could go anywhere

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how niantic evolved pokemon go for the year no one could go anywhere

Pokémon GO was created to encourage players to explore the world while coordinating impromptu large group gatherings — activities we’ve all been encouraged to avoid since the pandemic began.

And yet, analysts estimate that 2020 was Pokémon GO’s highest-earning year yet.

By twisting some knobs and tweaking variables, Pokémon GO became much easier to play without leaving the house.

Niantic’s approach to 2020 was full of carefully considered changes, and I’ve highlighted many of their key decisions below.

Consider this something of an addendum to the Niantic EC-1 I wrote last year, where I outlined things like the company’s beginnings as a side project within Google, how Pokémon Go began as an April Fools’ joke and the company’s aim to build the platform that powers the AR headsets of the future.

Hit the brakes

On a press call outlining an update Niantic shipped in November, the company put it on no uncertain terms: the roadmap they’d followed over the last ten-or-so months was not the one they started the year with. Their original roadmap included a handful of new features that have yet to see the light of day. They declined to say what those features were of course (presumably because they still hope to launch them once the world is less broken) — but they just didn’t make sense to release right now.

Instead, as any potential end date for the pandemic slipped further into the horizon, the team refocused in Q1 2020 on figuring out ways to adapt what already worked and adjust existing gameplay to let players do more while going out less.

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Turning the dials

As its name indicates, GO was never meant to be played while sitting at home. John Hanke’s initial vision for Niantic was focused around finding ways to get people outside and playing together; from its very first prototype, Niantic had players running around a city to take over its virtual equivalent block by block. They’d spent nearly a decade building up a database of real-world locations that would act as in-game points meant to encourage exploration and wandering. Years of development effort went into turning Pokémon GO into more and more of a social game, requiring teamwork and sometimes even flash mob-like meetups for its biggest challenges.

Now it all needed to work from the player’s couch.

The earliest changes were those that were easiest for Niantic to make on-the-fly, but they had dramatic impacts on the way the game actually works.

Some of the changes:

  • Doubling the players “radius” for interacting with in-game gyms, landmarks that players can temporarily take over for their in-game team, earning occupants a bit of in-game currency based on how long they maintain control. This change let more gym battles happen from the couch.
  • Increasing spawn points, generally upping the number of Pokémon you could find at home dramatically.
  • Increasing “incense” effectiveness, which allowed players to use a premium item to encourage even more Pokémon to pop up at home. Niantic phased this change out in October, then quietly reintroduced it in late November. Incense would also last twice as long, making it cheaper for players to use.
  • Allowing steps taken indoors (read: on treadmills) to count toward in-game distance challenges.
  • Players would no longer need to walk long distances to earn entry into the online player-versus-player battle system.
  • Your “buddy” Pokémon (a specially designated Pokémon that you can level up Tamagotchi-style for bonus perks) would now bring you more gifts of items you’d need to play. Pre-pandemic, getting these items meant wandering to the nearby “Pokéstop” landmarks.

By twisting some knobs and tweaking variables, Pokémon GO became much easier to play without leaving the house — but, importantly, these changes avoided anything that might break the game while being just as easy to reverse once it became safe to do so.

GO Fest goes virtual

GO Fest 2017

Like this, just … online. Image Credits: Greg Kumparak

Thrown by Niantic every year since 2017, GO Fest is meant to be an ultra-concentrated version of the Pokémon GO experience. Thousands of players cram into one park, coming together to tackle challenges and capture previously unreleased Pokémon.

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Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate

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A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

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The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.


Source: https://www.pcmag.com/articles/google-translate-vs-chatgpt-which-is-the-best-language-translator

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Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users

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Beginning in April, Gmail senders bombarding users with unwanted mass emails will encounter a surge in message rejections unless they comply with the freshly minted Gmail email sender protocols, Google cautions.

Fresh Guidelines for Dispatching Mass Emails to Gmail Inboxes In an elucidative piece featured on Forbes, it was highlighted that novel regulations are being ushered in to shield Gmail users from the deluge of unsolicited mass emails. Initially, there were reports surfacing about certain marketers receiving error notifications pertaining to messages dispatched to Gmail accounts. Nonetheless, a Google representative clarified that these specific errors, denoted as 550-5.7.56, weren’t novel but rather stemmed from existing authentication prerequisites.

Moreover, Google has verified that commencing from April, they will initiate “the rejection of a portion of non-compliant email traffic, progressively escalating the rejection rate over time.” Google elaborates that, for instance, if 75% of the traffic adheres to the new email sender authentication criteria, then a portion of the remaining non-conforming 25% will face rejection. The exact proportion remains undisclosed. Google does assert that the implementation of the new regulations will be executed in a “step-by-step fashion.”

This cautious and methodical strategy seems to have already kicked off, with transient errors affecting a “fraction of their non-compliant email traffic” coming into play this month. Additionally, Google stipulates that bulk senders will be granted until June 1 to integrate “one-click unsubscribe” in all commercial or promotional correspondence.

Exclusively Personal Gmail Accounts Subject to Rejection These alterations exclusively affect bulk emails dispatched to personal Gmail accounts. Entities sending out mass emails, specifically those transmitting a minimum of 5,000 messages daily to Gmail accounts, will be mandated to authenticate outgoing emails and “refrain from dispatching unsolicited emails.” The 5,000 message threshold is tabulated based on emails transmitted from the same principal domain, irrespective of the employment of subdomains. Once the threshold is met, the domain is categorized as a permanent bulk sender.

These guidelines do not extend to communications directed at Google Workspace accounts, although all senders, including those utilizing Google Workspace, are required to adhere to the updated criteria.

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Augmented Security and Enhanced Oversight for Gmail Users A Google spokesperson emphasized that these requisites are being rolled out to “fortify sender-side security and augment user control over inbox contents even further.” For the recipient, this translates to heightened trust in the authenticity of the email sender, thus mitigating the risk of falling prey to phishing attempts, a tactic frequently exploited by malevolent entities capitalizing on authentication vulnerabilities. “If anything,” the spokesperson concludes, “meeting these stipulations should facilitate senders in reaching their intended recipients more efficiently, with reduced risks of spoofing and hijacking by malicious actors.”

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Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches

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Google AI Chatbot Gemini

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.

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While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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