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A rare sealed hangtag copy of a 1st production Castlevania has been sold for $90,100, making this one of the highest-priced auctions for a raw boxed video game.
There were 130 bids in total and the item started at $37,000 on eBay from a seller located in Frisco, Texas.
The 1987 release was described as being in ‘Brand New’ condition on the listing, a label that is reserved for items that have never been opened or removed from the manufacturer’s sealing.
With the original $27.87 sticker price tag still on the game, the buyer has paid a pretty penny to get their hands on the Japanese classic. The happy buyer then went on to leave feedback for the seller: “The best eBay transaction I’ve ever had. Awesome seller and easy to deal with.
“Thank you for an amazing transaction. Five stars all the way.”
With many left wondering who took the win for the rare Castlevania, it wasn’t known whether this person would reveal themselves or if the sale would remain anonymous.
Then, a few weeks after the listing closed and in the first week of April, the person who paid the staggering amount came forward on Instagram under the username ‘minus_worlds’. He took to the social media platform to share a photo of the game fresh out of the mail.
The gamer has spent the last couple of years sharing his purchases and video game collection. The account is dedicated to playing, collecting, selling, and trading with a focus on all things retro.
Nostalgia wins the bidding war
The two photos of the Castlevania game are captioned with: “The search is over after 23 years.”
After searching for over two decades, the gamer thought they’d previously missed the opportunity to re-purchase it: “I resigned to never being able to add this grail after years of searching.
“But, everything just came together for a childhood friend and I this week as we were able to obtain this absolute beauty.
“This was the first game my mom ever bought me. I still remember the phone call we made to buy it. It’s a core memory, as is this past week.”
Featured Image: Via Instagram User Minus_Worlds
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Hands up who thought the popular browser game Infinite Craft was original? Wrong, it takes most of its ideas from a game called Little Alchemy and Little Alchemy 2, and both are now soaring in popularity due to the success of the slightly more unhinged Infinite Craft.
While both games are similar in many ways, Little Alchemy does require different recipe mixes for its elements. It also only has 720 elements to find making it infinitely more completeable for people of that kind of disposition.
As with Infinite Craft, creating Life and indeed Humanity are key building blocks to getting further in the game, so that is what we shall be looking at right here.
How to craft Life and Humans
If you have come to Little Alchemy via Infinite Craft you know the score here. We need to mix up lots of different elements to get to our end goal. Many are similar to what we needed to do in Neal.fun’s game but as this one is a few years older there is not as much variation.

Following the recipe below will get us to both Life and then Human. Both of which can be used to greatly enhance our inventory and encyclopedia.
Air + Air = Pressure
Earth + Pressure = Stone
Water + Earth = Mud
Mud + Stone = Clay
Water + Water = Puddle
Water + Puddle = Pond
Water + Pond = Lake
Water + Lake = Sea
Fire + Earth = Lava
Lava + Sea = Primordial Soup
Earth + Lava = Volcano
Volcano + Primordial Soup = Life
Life + Clay = Human
Many of the same techniques can be used from Infinite Craft, adding water to lake for example. The key is to get to Primordial Soup and then the world is your oyster.
How to play Little Alchemy 2
You can download Little Alchemy 2 on your iPhone or Android device via the App Stores on both. You can also join in the fun on a PC in a browser, just like Infinite Craft by heading straight to the Little Alchemy 2 website.
Featured Image: AI-Generated by Ideogram
The post How to make Life and Humans in Little Alchemy 2 appeared first on ReadWrite.

Google has unveiled the details of a new version of its data center artificial intelligence chips and announced an Arm-based central processor.
An Arm processor is a type of CPU that uses the RISC architecture, simplifying instructions the computer has to process. Google’s Tensor Processing Units (TPUs) are one of the only alternatives to Nvidia’s sophisticated AI chips. However, developers can only use them via Google’s Cloud Platform and cannot purchase them directly.
However, Google’s new Axion CPU will first support the company’s AI operations before becoming available to Google Cloud’s business clients later this year. The company stated that its performance is better than that of x86 chips and general-purpose Arm chips in the cloud. The Axion chips will be used to run YouTube ads, power the Google Earth Engine, and support various other Google services.

And @ThomasorTK is announcing #Axion processors – @Google’s first @ARM based chip – sees already 60% better energy efficiency than x86 #GoogleCloudNext pic.twitter.com/JpEdpA7oNd
— @GoogleCloud #GoogleCloudNext Holger Müller #AI (@holgermu) April 9, 2024

The Axion Arm-based CPU will deliver 30 per cent improved performance over “general-purpose Arm chips” and outperform Intel’s current processors by 50 per cent.
“We’re making it easy for customers to bring their existing workloads to Arm,” Google Cloud’s vice president and general manager of compute and machine learning infrastructure, Mark Lohmeyer, told Reuters. “Axion is built on open foundations but customers using Arm anywhere can easily adopt Axion without re-architecting or re-writing their apps.”
Lohmeyer also stated on a blog that the tech giant is improving its TPU AI chips: “TPU v5p is a next-generation accelerator that is purpose-built to train some of the largest and most demanding generative AI models.” The Alphabet subsidiary announced that the new TPU v5p chip is designed to operate in pods containing 8,960 chips, delivering twice the raw performance of the previous TPU generation. The TPU v5p is already available via Google’s cloud.
Google’s new cloud AI Hypercomputer architecture features
Google stated it has made significant improvements to its hypercomputer architecture, focusing on performance-optimized hardware enhancements. This includes the general availability of Cloud TPU v5p and A3 Mega VMs, which are powered by NVIDIA H100 Tensor Core GPUs. These updates are said to offer higher performance for large-scale training and come with enhanced networking capabilities.
It has optimized its storage portfolio for AI workloads with the introduction of Hyperdisk ML, a new block storage service designed for AI inference/serving workloads. New caching capabilities in Cloud Storage FUSE and Parallelstore have also been introduced, improving training and inferencing throughput and latency.
On the software front, Google has introduced several open source developments. This includes JetStream, a throughput- and memory-optimized inference engine for large language models (LLMs), which provides higher performance per dollar on open models like Gemma 7B.
Google is also introducing new flexible consumption options to better accommodate varying workload needs. This includes the Dynamic Workload Scheduler, which features a calendar mode for start time assurance and a flex start mode designed for optimized economics, further enhancing the efficiency and flexibility of Google’s cloud computing offerings.
Featured image: Canva
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Meta has confirmed that it is releasing its new open-source large language model (LLM) within the next month, according to reports.
TechCrunch reported that at an event in London on Tuesday (March 10), Meta’s president of global affairs, Nick Clegg, said, “Within the next month, actually less, hopefully in a very short period of time, we hope to start rolling out our new suite of next-generation foundation models, Llama 3.
“There will be a number of different models with different capabilities, different versatilities [released] during the course of this year, starting really very soon,” he added.
The Information originally claimed that a smaller version of Llama 3 would be released as early as next week, with the complete open-source model still set to launch in July. This version will be capable of competing with Claude 3 and GPT-4.
Chris Cox, Meta’s Chief Product Officer, added that the plan involves using Llama 3 to power a variety of Meta’s products.
The announcement comes as Meta attempts to catch up in the hyper-competitive world of generative AI. Its predecessor, Llama 2, was released in July 2023 and faced criticism for its limitations.
Joelle Pineau, Vice President of AI Research, stated, “Our objective is to evolve a Llama-powered Meta AI into the world’s most useful assistant. However, there’s still a significant amount of work needed to achieve this goal.”
However, Meta’s chief AI scientist Yann LeCun believes that Joint Embedding Predictive Architecture (JEPA) is the answer rather than generative AI. According to Meta, unlike generative approaches that try to fill in every missing pixel, JEPA has the flexibility to discard unpredictable information, which leads to improved training and sample efficiency.

Right. That’s why we need JEPA world models and use them for planning to fulfill a specified goal. https://t.co/8TI2NGRPvj
— Yann LeCun (@ylecun) April 7, 2024

What is Llama 3?
Llama 3, a large language model, will be available in sizes ranging from the very small, designed to compete with models such as Claude Haiku or Gemini Nano, to larger versions fully equipped for responses and reasoning, similar to GPT-4 or Claude Opus.
Details about Llama 3 remain scarce, however, it is expected that it will follow the previous version’s footsteps by being open source and is anticipated to be multimodal, understanding both visual and text inputs.
It is thought that Llama 3 will come in various versions and sizes, with the smallest having 7 billion parameters and the largest having around 140 billion parameters. However, this still falls short of the trillion-plus parameters that were used to train GPT-4.
Featured image: Canva
The post Meta will release Llama 3 LLM to compete with GPT-4 appeared first on ReadWrite.

PrizePicks have announced an extension to their partnership with the Atlanta Braves as they sign on for the 2024 season.
The fantasy sports operator has been working alongside the baseball team since 2020 and announced the news of the contract on Tuesday (April 9).
Unlike in the previous year, the sports operator will gain access to VIP experiences throughout the season. This will include a ‘Pick of the Game’ that will be featured on the Braves Radio Network pregame radio show for all 162 games.
The operator will be more visible at the games, with out-field LED signage and signs throughout Truist Park, the home stadium of the Atlanta Braves.
“We are thrilled to continue our ever-growing relationship with the Atlanta Braves,” said Adam Wexler, PrizePicks CEO and Co-founder. “As a homegrown company born in Atlanta, it is a priority for us at PrizePicks to engage with local fans by continuing to bring amazing experiences to Braves Country.”
PrizePicks is the largest skill-based daily fantasy sports operator and the fastest-growing sports company in North America, according to data from 2023.
The Senior Vice President of Corporate and Premium Partnerships at the Atlanta Braves, Jim Allen, described them as being a “valued partner for years.”
“They are the leader in their industry and a prominent local Atlanta business, and we are happy to extend our relationship with them for the 2024 season.”
Investment into new headquarters is made, opening 1,000 jobs in Atlanta
On April 4, PrizePicks publicized its plans to expand operations through a new 33,000-square foot Atlanta Headquarters.
This will be located in the Star Metals Building in Midtown Atlanta and comes at a time when the company commits to growing its workforce by 1,000 new jobs over the next seven years.
The economic impact of these opportunities is said to be $25M to the state of Georgia. It’s not yet known which departments the jobs will sit in and when the first stage of hiring will begin.
Featured Image: Photo by Clayton Malquist on Unsplash
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