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Considering Apple has a reputation for releasing product updates every couple of years, it is somewhat surprising that we’re yet to be treated to the second generation of the hugely popular Apple AirPods Max.
The AirPods Max represented Apple’s first foray into the over-ear headphones market when they launched in 2020, having already taken the wireless earbud market by storm with the AirPods and AirPods Pro.
A sublime blend of reliable battery life, comfort, cinematic spatial audio, incredible sound quality and beautiful design made the Airpods Max the most popular headphones on the market. Even at the high-end price of £549.
However, in what is a little out of character for Apple, fans are still patiently waiting for the second generation Apple Airpods Max. Current rumors, though, suggest the wait may be over pretty soon.

When will Apple AirPods Max 2 arrive?
There are no concrete dates for when Apple fans can get their hands on the AirPods Max 2, but a few rumors are circulating that we might be able to expect a new Max edition in the latter stages of 2024.
That is according to Apple analyst Ming-Chi Kuo, who claimed earlier this year that a new edition of the AirPods Max is likely to launch alongside a newer, more affordable version of earbuds, which he believes is due later in 2024.

(4/5)The next-generation AirPods will likely begin mass shipments in 2H24 or 1H25, including more affordable AirPods (with Apple targeting a price of $99) and new AirPods Max, which will be assembled by Luxshare ICT and Hon Teng.
— 郭明錤 (Ming-Chi Kuo) (@mingchikuo) January 12, 2023

Apple has a history of making us wait for AirPods Max releases, though. Before officially launching in December, it was expected they would debut a couple of months earlier alongside the launch of the iPhone 12. That didn’t happen due to “complications” and fans were made to wait a couple more months.
But a three-year wait for a fresh upgrade is unusual, which is fuelling rumors of an imminent announcement at some stage in 2024.
How will the Apple AirPods Max 2 look?
Whatever upgrades are in line for the Airpods Max 2, you can bet the overall design, look and feel will be sleek, comfortable and eye-catching. That’s what we’ve come to expect from Apple ever since the launch of the iMac G3 in 1998.
As we’re still relatively in the dark about the next edition of the Max, we’re having to rely on insider speculation to get a picture of what we might expect when they do eventually arrive.
Bloomberg’s Mark Gurman has fueled many of the rumors in this area with several comments in an October 2023 newsletter, in which he also echoes the views of Kuo regarding a potential release date. He mostly hints at new colors and the introduction of USB-C charging.
The color range
Firstly, there’s the color range. The Airpods Max is available in Silver, Blue, Space Grey, Pink and Green. Gurman believes an “AirPods Max refresh with new colors” is on the horizon. That has fuelled rumors that the tech giant are considering introducing Yellow, Orange and Purple to the range, while it’s also being whispered that a Product (Red) edition. Some believe the new colors may be in sync with those of the upcoming iPhone 16, which is also expected to debut later this year.
USB charging
Elsewhere, the rumored introduction of USB-C charging is arguably the least surprising rumor of all. Apple announced the USB-C connections on the new iPhone 15 and charging cases for the Airpods Pro 2 in December 2023, so it’s a reasonable assumption to make that it will be present in all Apple products in the future.
Touch controls
Meanwhile, there is talk that Apple is making changes to the Max’s control mechanism, moving closer towards touch controls instead of continuing with the existing Digital Crown. This may come as music to the ears (pun intended) to current Max owners who find themselves knocking the Digital Crown when adjusting them.
The carry case
And finally, on to the carry case. While the AirPods Max’s design wowed fans, their protective case has come under some criticism. Particularly for not being very protective. Thankfully, a patent uncovered in the summer of 2022, appears to suggest Apple is working on a more substantial and durable case that utilizes a magnetic clasp.
This points towards an actual case, as opposed to what can only be described as a wrap-around cover we have today.
What are the Apple Airpods Max 2 specs?
The first edition AirPods Max arrived packed with top-of-the-range specifications and features, including active noise-cancellation (ANC), adaptive EQ, spatial audio with dynamic head-tracking and two H1 Apple chips.
That’s quite a lot to live up to and improve on in a second edition, but rumors point towards Apple working on making several significant improvements.
Firstly, there are improvements to ANC, with a recent AirPods Max patent referring to “audio howl” detection, with Apple looking to improve on ways to better mitigate unwanted feedback that is typically created by ANC microphones.
Elsewhere, there are whispers that Apple might be working on a way to deliver wireless lossless audio via better-than-Bluetooth audio transmission technology. If true and, of course, if it’s included in the Max, this will likely revolutionize the quality of portable wireless audio.
There is currently no noise surrounding what chip the Airpods Max 2 will use, but we can make a reasonable assumption that the H2 chip might be introduced to replace the H1 chips in the first edition Max. The H2 chip is already incorporated in the Airpods Pro 2. That said, there a no guarantees.
Other rumored features include the new “Find My” feature, which will allow owners to locate their headphones via the use of their iPhone, and a likely IPX rating, which means the Airpods Max 2 will be more suited to wetter conditions, such as rain, splashes and even sweat, for those that use their cans in the gym.
How much will Apple AirPods Max 2 cost?
Eyebrows were raised when the first-generation Airpods Max launched with a hefty £549 price tag, but it still didn’t stop people rushing to buy them. They sold out almost instantly, with the waiting list peaking at around 14 weeks.
There is nothing on the rumor mill to suggest Apple will launch the second-generation Max at a lower price point, so we should still expect to pay a top-of-the-range fee for what is going to be a top-of-the-range product.
Some fans have expressed wishes for a cheaper model to be released alongside the new Max to give fans the option depending on their budget, which Apple has previous with when it comes to their iPhone, Macbook, iPad and Apple Watch ranges.
However, that’s just people expressing their wishes as opposed to a credible rumor at this stage.
Featured Image: Photo by Super Snapper on Unsplash.
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There are so many buzzwords in the tech world these days that keeping up with the latest trends can be challenging. Artificial intelligence (AI) has been dominating the news, so much so that AI was named the most notable word of 2023 by Collins Dictionary. However, specific terms like ‘machine learning’ have often been used instead of AI.
Introduced by American computer scientist Arthur Samuel in 1959, the term ‘machine learning’ is described as a “computer’s ability to learn without being explicitly programmed.”
So, what is the difference between AI and machine learning?
For one, machine learning (ML) is a subset of artificial intelligence (AI). While they are often used interchangeably, especially when discussing big data, these popular technologies have several distinctions, including differences in their scope, applications, and beyond.
What is artificial intelligence?
Most people are now aware of this concept. Still, artificial intelligence actually refers to a collection of technologies integrated into a system, allowing it to think, learn, and solve complex problems. It has the capacity to copy cognitive abilities similar to human beings, enabling it to see, understand, and react to spoken or written language, analyze data, offer suggestions, and beyond.
What is machine learning?
Meanwhile, machine learning is just one area of AI that automatically enables a machine or system to learn and improve from experience. Rather than relying on explicit programming, it uses algorithms to sift through vast datasets, extract learning from the data, and then utilize this to make well-informed decisions. The learning part is that it improves over time through training and exposure to more data.
‘Machine learning models’ are the results or knowledge the program acquires by running an algorithm on training data. The more data used, the better the model’s performance.
How are machine learning and AI related?
Machine learning is an aspect of AI that enables machines to take knowledge from data and learn from it. In contrast, AI represents the overarching principle of allowing machines or systems to understand, reason, act, or adapt like humans.
Hence, think of AI as the entire ocean, encompassing various forms of marine life. Machine learning is like a specific species of fish in that ocean. Just as this species lives within the broader environment of the ocean, machine learning exists within the realm of AI, representing just one of many elements or aspects. However, it is still a significant and dynamic part of the entire ecosystem.
What are the differences between machine learning and AI?
Machine learning cannot impersonate human intelligence, which is not its aim. Instead, it focuses on building systems that can independently learn from and adapt to new data through identifying patterns. AI’s goal, on the other hand, is to create machines that can operate intelligently and independently, simulating human intelligence to perform a wide range of tasks, from simple to highly complex ones.
For example, when you receive emails, your email service uses machine learning algorithms to filter out spam. The ML system has been trained on vast datasets of emails, learning to distinguish between spam and non-spam by recognizing patterns in the text, sender information, and other attributes. Over time, it adapts to new types of spam and your personal preferences — like which emails you mark as spam or not — continually improving its accuracy.
In this scenario, your email provider may use AI to offer smart replies, sort emails into categories (like social, promotions, primary), and even prioritize essential emails. This AI system understands the context of your emails, categorizes them, and suggests short responses based on the content it analyzes. It mimics a high level of understanding and response generation that usually requires human intelligence.
What are the 4 types of machine learning?
There are three main types of machine learning and some specialized forms, including supervised, unsupervised, semi-supervised, and reinforcement learning.

Machine learning algorithms are classified into 4 types: 1. Supervised 2. Unsupervised 3. Semi-supervised 4. Reinforcement
1. Supervised learning, the algorithm learns from a labeled dataset where both input features and their corresponding target labels are provided. The… pic.twitter.com/2bwW3qFrkB
— Danny.28 (@drifterddm) May 29, 2023

In supervised learning, the machine is taught by an operator. The user supplies the machine learning algorithm with a recognized dataset containing specific inputs paired with their correct outputs, and the algorithm has to figure out how to produce these outputs from the given inputs. Although the user is aware of the correct solutions, the algorithm needs to identify patterns, all while learning from them and making predictions. If the predictions have errors, the user has to correct them, and this cycle repeats until the algorithm reaches a substantial degree of accuracy or performance.
Semi-supervised learning falls between supervised and unsupervised learning. Labeled data consists of information tagged with meaningful labels, allowing the algorithm to understand the data, whereas unlabeled data does not contain these informative tags. Using this mix, machine learning algorithms can be trained to assign labels to unlabeled data.
Unsupervised learning involves training the algorithm on a dataset without explicit labels or correct answers. The goal is for the model to identify patterns and relationships in the data by itself. It tries to learn the underlying structure of the data to categorize it into clusters or spread it along dimensions.
Finally, reinforcement learning looks at structured learning approaches, in which a machine learning algorithm is given a set of actions, parameters, and goals. The algorithm then has to navigate through various scenarios by experimenting with different strategies, assessing each outcome to identify the most effective approach. It employs a trial-and-error approach, drawing on previous experiences to refine its strategy and adjust its actions according to the given situation, all to achieve the best possible result.
How AI and machine learning apply in the real world
In financial contexts, AI and machine learning serve as essential tools for tasks like identifying fraudulent activities, forecasting risks, and offering enhanced proactive financial guidance. Apparently, AI-driven platforms can now offer personalized educational content based on an individual’s financial behavior and needs. By delivering bite-sized, relevant information, these platforms ensure users are well-equipped to make informed financial decisions, leading to better credit scores over time. Nvidia AI posted on X that generative AI was being incorporated into curricula.

Learn how educators are integrating #GenerativeAI, Design & Sim into their curricula. Join professors from @UTAustin & @UW as they share insights on revolutionizing education with immersive learning on NVIDIA’s Omniverse platform.
Mar. 21 #GTC24 https://t.co/6vcNiH6BuU pic.twitter.com/c04tf6J06a
— NVIDIA AI (@NVIDIAAI) February 27, 2024

During the Covid-19 pandemic, machine learning also gave insights into the most urgent events. They are also powerful weapons for cybersecurity, helping organizations protect themselves and their customers by detecting anomalies. Mobile app developers have actively integrated numerous algorithms and explicit programming to make their apps fraud-free for financial institutions.
Featured image: Canva
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Dragon’s Dogma 2 (DD2) ramped up excitement this week by releasing its character creator as a standalone download weeks ahead of the game’s launch. We’ve rounded up all the reasons we have to be excited about the game and all we know so far so dive in to get really hyped.
What kind of game is Dragon’s Dogma 2?
Like the original, DD2 is a third-person action RPG where the player takes charge of The Arisen to hunt down legendary foes and face an epic story of dogma and dragon slaying. The player will be helped by non-playable characters called Pawns. Pawns have adaptive AI and will learn as you go, which can be useful…if you teach them good habits. If you drink too many healing potions you might find your Pawns gulping them down like they are going out of fashion.
How big will the game be?
The game’s director Hideaki Itsuno has stated that the map of Dragon’s Dogma 2 would be four times larger than the map in the original game. In a subsequent interview, Itsuno discussed the game’s limited fast travel system. Players can get ox carts between some settlements, but you never know what monsters you might be faced with while en route. “While riding one, you might find the path blocked by goblins and have no choice but to get off and join the battle. Then as you do, a Griffin might swoop in and destroy the entire cart with one blow, forcing you to walk the rest of the way while cursing its name,” said Itsuno. He explained that none of these encounters are scripted and mentioned Rockstar’s games as inspiration for dynamic, emergent gameplay. “Travel is boring? That’s not true. It’s only an issue because your game is boring.”
Other gameplay elements we know
It has been revealed that in-game quest markers will be kept to an absolute minimum. Don’t expect to see yellow exclamation points above the heads of NPCs who have a quest, or dotted lines on the map leading you to exactly where you need to go to complete the quest. DD2 takes a more traditional approach, with characters giving you instructions and directions. Or maybe you’ll get lucky and your Pawn will know where to go. Pawns are also eagle-eyed and are designed to point out any areas of interest you’re walking past. Taking after three of the most successful games of recent years (Zelda Breath of the Wild, Elden Ring, and Zelda Tears of the Kingdom) this is sure to lead to organic and rewarding gameplay.
Capcom has worked hard to make sure gameplay and combat will be dynamic and engaging. Break down a dam to wash your foes away. Cut off an enemy’s head and wield it as a weapon. Cut down a bridge to enable a quick getaway – but be careful because next time you need to go that way, you’ll have to find a way around the broken bridge.
One key thing to be aware of is that you can permanently kill NPCs in DD2, whereas the first game had them respawning after some in-game time had passed. So don’t swing your sword about too carelessly.

NPCs no longer respawn in Dragon’s Dogma 2. If an NPC dies, they go to the morgue. While they’re in the morgue you can wakestone them back to life, but they only stay there a few days before being buried. At that point that NPC is gone for the rest of the game.#DragonsDogma2 #DD2 https://t.co/wTKNGe7KXx
— Chainsaw McFacepunch (@MrMcFacepunch) March 6, 2024

Will Dragon’s Dogma 2 have multiplayer?
DD2 will be purely single-player with no multiplayer gameplay elements. However, the Pawns that you create become part of an online database of Pawns that other players will be able to recruit in their games. Likewise, when you visit the Nexus you can recruit Pawns created by other players. You can turn this feature off and recruit developer-made Pawns if you prefer.

Can you have multiple saves/characters at once?
Like in the original Dragon’s Dogma, DD2 will have only one save file. If you want to start a new character or playthrough you’ll have to delete your previous one. While this can encourage exploration and make decisions more impactful because you can’t go back and see what might have happened, some players will be frustrated at not being able to dabble in multiple different character classes and playstyles.
Is the frame rate capped?
This has been a concern for console gamers but director Hideaki Itsuno took to Twitter to confirm that framerates for the game will be uncapped and it aims to rest at around 60fps.
When will Dragon’s Dogma 2 release?
Dragon’s Dogma 2 is due to release on March 22, 2024, barring any unforeseen delays. It will cost $70, and there is a deluxe edition available for $80 which includes a variety of in-game items.
Featured image credit: Capcom
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DraftKings has announced the launch of its online sportsbook in North Carolina, as of 11 March 2024.
A company press release detailed the latest expansion for the gambling platform, representing its proliferation across 27 US states as well as Ontario in Canada. The arrival of online and mobile DraftKings betting in North Carolina follows on from an agreement earlier this year with NASCAR, which opened up its initial foray into digital sports entertainment and gaming in the state.
The online sportsbook platform will provide users with features such as same-game parlays, in-game betting and special odds boosts.
With responsible gambling protocols in mind, the platform will operate within the regulatory framework which includes safeguards on each account such as deposit limits, help resources and a ‘My stat sheet’ tracker to monitor the betting activity.
The launch comes on the back of dialogue and collaboration with local stakeholders and the relevant authorities to bring Draft Kings in line with the sports entertainment landscape in the Southeastern state.
Official reaction to the launch
Matt Kalish, DraftKings North America President expressed his satisfaction with the latest growth for the brand.
“With the NCAA Tournament right around the corner and the NASCAR season in full throttle, we are thrilled to be launching our top-rated sportsbook app in North Carolina,” he said.
“The Tar Heel State is home to a passionate fanbase and some of the most iconic college basketball programs of all time, making this an exciting time to introduce legalized online sports betting. We’re proud to be working alongside NASCAR as our market access partner and look forward to enhancing the fan experience across North Carolina with a fun, safe and seamless sports betting product.”
Another recent addition to the gambling market, as North Carolina embraces mobile sports betting, is the official partnership between FanDuel and NFL side Carolina Panthers.
That launch is also set for 11 March, after the green light was granted by the North Carolina State Lottery Commission, but fans aged 21 and over can pre-register on the Sportsbook app now.
Featured credit:  andres/pexels
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Temu, the bargain, e-commerce, too-good-to-be-true items merchant, has a strong relationship with Meta. According to the Wall Street Journal, it spent $2 billion alone on Facebook and Instagram ads. The outlet also claims that it was the number one advertiser by revenue for Meta. And when it comes to Google ads, Temu is not too shabby on that front either, as the WSJ report also names it as one of the platform’s top five advertisers.
While a Temu advertiser disputed this $2 billion sales figure, it also refused to disclose its exact spending to the outlet. But one event where their spending got especially elaborate was the Superbowl. This year, the game amassed over 123 million, and Temu certainly made the most of that, as Quartz reports that Temu had four 30-second advertisements — which, according to Ad Age, cost approximately $7 million each.
What is Temu?

With its relentless advertising, you’d be forgiven for thinking that Temu has been around longer than it has been — but it was only founded back in 2022 in Boston, Massachusetts. On the Temu website, the company describes itself as “an e-commerce company that connects consumers with millions of merchandise partners, manufacturers and brands with the mission to empower them to live their best lives.”
This means that, in other words, Temu can save a lot of money by dispatching products directly from factories in China to consumers. By cutting out a middle-man, the company can save on expensive tariffs, which means that its resultant products are eye-wateringly cheap.
It’s worth noting that Temu doesn’t manufacture products itself, and this has caused issues for the company in the past because there’s no way of checking to see if it’s compliant with anti-forced labor laws. This means that the products they sell may well be the result of forced labor, so while it’s certainly cheap, there’s arguably a bigger price to pay for it all.
Image Credits: Photo by RoseBox رز باکس on Unsplash
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