Major Bummer for Students: Apple Hikes Price of MacBook Neo


Apple raised prices across the board on Thursday, pointing the finger at RAMageddon for what Apple CEO Tim Cook called an “unavoidable” response to rising memory and storage prices as demand for these components surged with the spread of AI data centers. The price hikes hit many Apple product lines, including the iPad, Mac, Apple TV, HomePod and VisionPro. Seemingly, only the iPhone and Apple Watch were spared.

What I’m most upset about is that Apple raised the price of its budget MacBook Neo. We finally got a MacBook built for student budgets, and in the blink of an eye, it’s gone. The $499 Neo student pricing lasted about as long as a semester. 

Only three-and-a-half months after Apple drastically reduced the entry point for the MacBook, it’s turned around and raised the price by $100. Now, the MacBook Neo starts at $699 at Apple, and students can get it for $599. (At the time of this writing, it’s still available for $590 at Amazon.)

The cost of the step-up model with Touch ID and double the storage also went up by $100. It now costs $799, or $699 with Apple’s education discount. (It’s still $690 at Amazon.)

Is it really the RAM?

Apple and other computer-makers point to the surge in demand for memory and storage from AI data centers, called RAMageddon, as the reason for rising component prices, which have forced them to hike the price of the computers they sell. But with only 8GB of RAM and a modest 256GB SSD, the baseline MacBook Neo doesn’t seem to merit a $100 increase. And given that the step-up model gets you only a 512GB SSD with no accompanying increase in memory, its $100 price hike feels steep, too.

I think Apple is hiding the real reason behind the Neo’s price hike: It sold through its initial supply of Neos that used leftover iPhone processors and now must incur the added cost of manufacturing new A18 Pro chips to meet Neo demand. 

As previously reported, Apple was preparing a new production run of the MacBook Neo, increasing the number of units to 10 million from its initial run, estimated at 5 to 6 million. And the math changes for Apple if it no longer has a stash of A18 Pro chips it can borrow for this new Neo run.

I suspect RAMageddon is a convenient excuse for Apple to cover the added costs to make new Neos. Or at least, it’s not the only reason for Apple raising the price of the Neo just a few months after its debut.

Apple did not immediately respond to a request for comment on this theory.

MacBook Neo lock button

It’ll now cost you $799 to turn that lock button into a Touch ID sensor.

Matt Elliott/CNET

Bigger increases for MacBook Air and Pro

What throws cold water on my Neo theory is that Apple slapped even larger price increases on the MacBook Air and Pro lines. The price of the MacBook Air went up by $200, and the MacBook Pro increased by $300. 

The 13-inch MacBook Air now starts at $1,299, and the 15-inch Air now starts at $1,499.

The 14-inch MacBook Pro now starts at $1,999, and the 16-inch Pro now starts at $2,999. 

The MacBook Air comes with a minimum of 16GB of RAM and 512GB SSD, and the MacBook Pro comes with a minimum of 16GB of RAM and a 1TB SSD. 

“We have never seen a component price increase this much, this quickly,” Apple said in the statement. “We have now reached a point where we need to begin raising prices on a number of products, including today’s increases for iPad and Mac.”

MacBook price increases

Model Old price New price
MacBook Neo $599 $699
13-inch MacBook Air $1,099 $1,299
15-inch MacBook Air $1,299 $1,499
14-inch MacBook Pro $1,699 $1,999
16-inch MacBook Pro $2,699 $2,999

Neo vs. Air

As much as it hurts for students and their parents to pay $100 more for a MacBook Neo for school, you could try to console yourself by comparing that increase to the new pricing for the MacBook Air. With the Neo jumping from $599 to $699, and the Air jumping from $1,099 to $1,299, the gap between the two has widened. The Neo now costs $600 less than the cheapest Air.

While that reasoning might help justify being forced to pay more for a MacBook Neo, the $100 price increase still hurts anyone who’s already facing the higher costs of higher education.

Apple M5 MacBook Air laptop in front of a house plant

The MacBook Air now starts at $1,299, a $200 increase from its previous price.

Matt Elliott/CNET

Other Macs are more expensive now, too

Apple’s Mac desktops weren’t spared. Pricing increased for the iMac, Mac Mini and Mac Studio.

Apple raised the price of the iMac by $200 to $1,499. It brought back the baseline M4 Mac Mini with 16GB of RAM and 256GB of storage that it discontinued in May, but it returned with a $200 increase. The M4 Pro model also got hit with a $200 price hike. 

Those increases pale in comparison to what the Mac Studio received. The M4 Max model now starts at $2,499, up $500. And if you’re sitting down, I’ll tell you what the Mac Studio with the M3 Ultra chip now costs. It starts at $5,299, a staggering rise in price of $1,300.

Mac desktop price increases

Model Old price New price
iMac $1,299 $1,499
Mac Mini (M4) $599 $799
Mac Mini (M4 Pro) $1,399 $1,599
Mac Studio (M4 Max): $2,499, up from $1,999 (+$500) $1,999 $2,499
Mac Studio (M3 Ultra): $5,299, up from $3,999 (+$1,300) $3,999 $5,299





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Microsoft Azure IoT Edge empowers the simple management and integration of Internet of Things (IoT) application areas that incorporate Microsoft Azure cloud services with on-premises computer equipment and service providers.

Microsoft Azure IoT Edge would’ve been comprised of the IoT Edge Runtime, which would have been installed on a computer or device. Such devices also might run Windows or Linux and require Docker to be configured. Eventually, the Azure IoT Edge Runtime utilizes Docker to run IoT Edge Modules on the device, with a connection to Microsoft Azure IoT Hub dictating which components to incorporate and implement.

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Azure IoT Edge Module:

With Azure IoT Edge, cloud compute abilities are propelled back to answer on edge devices via the use of IoT Edge Modules. An Edge Module is the lowest level of compute managed by IoT Edge Runtime. These modules could include Azure services like Azure Stream Analytics, or they could contain your own domain-specific module code required by your IoT Edge solution.

The development, construction, and deployment of  the IoT Edge modules has been divided into various logical steps:

  • Creating an IoT Edge Module – An IoT Edge Module will be created by writing it in any supported language such as C#, C, or others. (Some modules, such as those for running Azure services on IoT Edge, are prebuilt by Microsoft.)
  • Module Build as well as Deployment to Docker Registry – The Module would be designed and implemented to the Docker Registry, includingDocker Hub. The IoT Edge Runtime could then be equipped to retrieve an Module image within a Docker Registry and implement it to each or even various IoT Edge devices.
  • Manage Device and Module Identities in Azure IoT IoT Hub – A device identity for the IoT Edge Device will be been built and managed in Azure IoT Hub One such device identity also included IoT Edge Module Ideologies in each of the Edge Modules implemented to the device, as well as module configurations to each other.
  • Install and activate the IoT Edge Runtime on your device(s) – The IoT Edge Device and the installed IoT Edge Runtime are set up to connect to the cloud via Azure IoT Hub or Azure Device Provisioning Service. When the device connects to Azure IoT Hub, it will automatically retrieve the device identity as well as any configured IoT Edge Module Identities and then begin running.

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Such steps to use the Device Identity and Edge Module Identifications to handle and configure the Azure IoT Edge Device(s) inside of Azure IoT Hub provide such a method for wirelessly managing Azure IoT Edge Devices. Merely reorganize the dimensional case or Edge Module Identities within Azure IoT Hub to start making upkeep or setup changes to the Azure IoT Edge Devices, and the updates are applied.Furthermore, Edge Devices are verified and approved remotely, making it just as simple to revoke a device’s access or retire older devices.

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Azure IOT Edge Offline Capabilities:

One advantage of using Edge Compute in an IoT solution is that it keeps the solution running even when the device(s) are disconnected or experiencing high network latency. Azure IoT Edge enables you to run custom code as well as Azure services on the local IoT Edge Device(s) that are part of a larger IoT solution.

The Edge Compute resources built with Azure IoT Edge that are locally connected have several advantages for any IoT solution:

  • Lower Latency Decisions – Because domain logic and even Azure services (such as Stream Analytics or Azure Functions) can run on-premises with an Azure IoT Edge Device, the solution can make decisions and take actions much more quickly and with lower latency.The interactions no longer have to make a round trip into Azure and back.
  • Offline Capability: The IoT Edge Device can operate while disconnected from Azure IoT Hub for a short period of time or for an extended period of time
  • Data Synchronization: With Azure IoT Edge’s offline capabilities, the IoT Edge Runtime will automatically save all IoT telemetry events on local device storage and then transmit that data to Azure IoT Hub when connectivity is restored. The length of time data is stored on the device (also known as Time-to-Live) can be customized for your IoT solution.
  • Lower Bandwidth usage: By leveraging Edge Compute to do even more computation for an IoT solution, less data and IoT device telemetry must be sent to the cloud. Furthermore, processing the data on-premises with Azure IoT Edge enables aggregates or overviews of the telemetry to be conveyed to the Azure IoT Edge when all telemetry events do not need to be sent to or stored in the cloud.

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Many Technology devices benefit from all of Azure IoT Edge’s ability. This is true whether the IoT Device also has sensors immediately mailing telemetry to Azure IoT Hub or if the IoT Edge Device is implemented as an IoT Gateway connected to various other IoT Sensor Devices.

Low latency, offline, and low network abilities, for instance, can greatly benefit industrial IoT scenarios. If large equipment can fail, having caused millions in damage or even serious bodily harm, and being allowed to achieve a specific objective with less latency is a great advantage!

Related Article: Future Scope of IoT

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Conclusion:

In the above blog post we discussed the Azure IoT Edge in a more detailed way. If You have any queries please drop them in the comments section, we will consider them and get back to you.

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