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Threat actors have long leveraged typosquatting as a means to trick unsuspecting users into visiting malicious websites or downloading booby-trapped software and packages. These attacks typically involve registering domains or packages with names slightly altered from their legitimate counterparts (e.g., goog1e.com vs. google.com). Adversaries targeting open-source repositories across

Threat actors have long leveraged typosquatting as a means to trick unsuspecting users into visiting malicious websites or downloading booby-trapped software and packages. These attacks typically involve registering domains or packages with names slightly altered from their legitimate counterparts (e.g., goog1e.com vs. google.com). Adversaries targeting open-source repositories across Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

Google Research (výzkumná divize Googlu) vyvinula nástroj využívající umělou inteligenci, který analyzuje satelitní a letecké snímky s cílem pomoci městům snižovat povrchové teploty. Nástroj například navrhuje vysazování stromů nebo používání reflexních povrchů, jako jsou takzvané „chladné střechy“ ...

Dnes tady máme rodinnou kooperativní hru hr, v níž povede společenstvo prstenu skrze všechna nebezpečenství a nástrahy až k Hoře osudu. Dokážete na závěr vhodit prsten do žáru hory, nebo se z vás stane druhý Isildur?

Depression doesn’t mean you’re always feeling low. Sure, most times it’s hard to crawl out of bed or get motivated. Once in a while, however, you feel a spark of your old self—only to get sucked back into an emotional black hole.

There’s a reason for this variability. Depression changes brain connections, even when the person is feeling okay at the moment. Scientists have long tried to map these alternate networks. But traditional brain mapping technologies average multiple brains, which doesn’t capture individual brain changes.

This week, an international team took a peek into the depressed mind. With brain imaging technology called precision functional mapping, they captured the brains of 135 people with depression for over a year and a half.

The largest brain mapping study of the disorder to date, the results revealed a curious change in the brain’s connections in people with depression—a neural network, usually involved in attention, nearly doubled its size compared to those without the condition. The increase remained even during periods when the person no longer felt low.

The brain signature isn’t just a neurobiological sign of depression—it could also be a predictor. When observed in the brain imaging data of nearly 12,000 children starting from nine years old, the expanded network predicted the onset of depression later in adolescence.

So far, brain imaging studies for depression have been “one size fits all,” in that studies compare averaged brain scans between people with or without depression, explained the team in their study.

With precision functional mapping, it’s possible to track individual brain trajectories as they change over time. In turn, this could lead to more nuanced insights into neural connections in depression and inspire more sophisticated and personalized brain implants to tackle the disorder.

To Dr. Caterina Gratton at the University of Illinois Urbana-Champaign, who was not involved in the work, the precise details from the brain scans are impressive. “Rather than reading a few pages of many books, we’re reading whole chapters,” she told Nature.

The Old Playbook

Scientists have long tried to decipher the brain networks underlying depression.

There have been successes. At the turn of this century, neurologist Dr. Helen Mayberg and colleagues spearheaded brain mapping studies that compared brains with the disorders and those without. They eventually pinpointed a region at the front of brain that hyperactivates in people with severe depression.

Given deep brain stimulation in the region—a technique where implanted electrodes zap dysfunctional circuits with brief pulses of electricity—some patients rapidly improved. Since then, neuroscientists have identified multiple brain networks involved in the disorder. However, larger trials of deep brain stimulation yielded mixed results.

Some patients didn’t respond to the treatment. But others experienced life-altering changes. In 2021, a woman named Sarah received a personalized brain implant. She had battled severe depression for years and had tried a range of medications. None of them worked. But the implant did. Fine-tuned to her brain’s unique electrical signals, for the first time in her life, Sarah had her depression under control. “I’m finally laughing,” she said at the time.

Sarah’s case highlighted two points for tackling the brain networks involved in depression. One, the disorder affects each brain differently. And two, depression is chronic, with ebbs and flows in mood. Imaging brain connection changes at just one point in time isn’t enough—what’s needed is to follow the brain’s functional changes over time.

Precision Mapping

There are many ways to track brain function, but a popular one is functional magnetic resonance imaging (fMRI). The technology tracks changes in blood flow in the brain—a proxy for activity—and builds a map of how different regions and brain connections “talk” to each other.

But our brains are snowflakes. Although brain networks look similar on average, each person slightly deviates. Precision mapping captures these individual differences, with previous studies showing that the size, shape, and location of neural networks can markedly differ, but are generally stable for each person. In other words, we all have a unique “brainprint.”

However, depression changes these dynamics as the disorder progresses. A single fMRI brain scan—a snapshot—can’t capture the brain’s trajectory over time.

The team tackled these problems head-on. In a first small study, they repeatedly imaged the brains of 6 people with depression—ranging from mild to severe—across 22 sessions. Precision mapping was also used for 37 people without the disorder.

By looking at brain activation patterns, “it was immediately apparent” that a brain network changed in people with depression, even without averaging the results. Dubbed the “salience network,” it relies on multiple brain regions to help us navigate the world with purpose. The network combines outside stimulation with an internal goal—say, make a cup of coffee for an early morning jolt. As a central networking hub in the brain, it lets us decide what to pay attention to.

In people with depression, the network expanded twice as much, compared to controls—in that more parts of the brain activated to support it.

Six people hardly represent the entire spectrum of depression. To validate their findings, the team turned to three existing datasets from Weill Cornell Medicine and Stanford University. Totaling 135 people with depression, the datasets captured detailed brain images and demographic and clinical information. Almost every person with depression showed a larger salience network. They also saw a similar brain pattern in an additional dataset of nearly 300 people with depression, who didn’t respond to antidepressant drugs.

Symptoms of depression ebb and flow. Does network expansion follow the pattern? In another test, they used precision fMRI to follow people with depression roughly every week for up to a year and a half. With each scan, the participants also reported their mood based on a standardized depression scale.

Regardless of current emotions, the salience network remained roughly the same size for each person. However, the strength of connections between the network’s components changed—decreasing when the person was actively depressed. Using AI to analyze these patterns, the team was able to predict—for any of the participants—if they might experience a depressive episode the following week.

The results suggest that an expanded salience network, and its inner connections, isn’t just a marker for depression after symptoms have already set in. It could also be a predictor. To test the idea, they tapped into the Adolescent Brain Cognitive Development (ABCD) dataset, the largest long-term study of brain development and health for children in the US. The ambitious project tracks nearly 12,000 children across the country, from nine years old to young adulthood.

By analyzing salience network expansion, the team identified 57 kids, aged 10 to 12 years old, who eventually developed depression a few years later. Their salience network was already far larger than similarly aged peers at their initial visit. If replicated in more children, it could be a feature that helps predict depression risk and allows early intervention.

For now, scientists don’t know why or how the network expands. It could be partly due to genetics, which plays a role in depression. Another reason could be the brain dials up the network during depressive episodes, recruiting more brain cells and resulting in the network’s growth. But the study shows the power of precision brain mapping over time.

The results “will open new avenues for understanding cause and effect” when it comes to brain changes and depression, wrote the team, “and for designing personalized, prophylactic treatments.”

Image Credit: Andrew Neel / Unsplash

V Kalifornském technologickém institutu (Caltech) představili chytrou roušku. Nechrání jen okolí nositele a jej samotného před nákazou, ale také důkladně analyzuje dech a na jeho základě pak detekuje aktuální zdravotní stav. Maska EBCare, což je zkratka pro „analýza kondenzátu vydechovaného ...

Qualcomm is reportedly exploring the possibility of acquiring parts of Intel’s chip design business to enhance its product portfolio. This potential move comes as Intel faces financial difficulties, prompting the company to consider divesting certain business units and assets, according to a Reuters report.

Qualcomm has been evaluating various parts of Intel’s design operations, with a particular interest in Intel’s client PC design business. However, other segments, such as Intel’s server division, are seen as less relevant to Qualcomm’s strategic goals, the report said citing sources.

While Qualcomm has not yet approached Intel regarding a deal, the discussions have been ongoing for months, and the plans could still change, insiders noted.

Queries to Qualcomm and Intel remained unanswered.

Acquiring Intel’s chip design business could offer Qualcomm a strategic opportunity to diversify its product offerings and expand beyond its mobile chip dominance. With AI becoming increasingly important, Intel’s expertise in PC chips could complement Qualcomm’s push into AI-driven computing.

“Qualcomm’s increasing interest in the PC chip business is no surprise,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “This addition will strengthen the Qualcomm-Microsoft relationship and build on the Surface Laptop and Pro tablet series.”

He further added, “The convergence of mobile and personal computing devices offers Qualcomm a significant opportunity to create optimized experiences across device types.”

It will be great news for Qualcomm who can now enter the PC segment, especially in the AI world, said Titus M, practice director at Everest Group. “However, the exact forms and shape remain unknown and are now down to pure speculations.”

This move comes as Qualcomm aims to strengthen its Snapdragon X series, which as Gogia notes would “sit very well” with Intel’s design capabilities, enhancing Qualcomm’s position in the AI PC space. Gogia also highlights Qualcomm’s potential to disrupt the market with aggressive pricing, posing a significant challenge to competitors like AMD and Apple.

Intel’s financial struggles and ongoing restructuring

Intel, facing mounting financial challenges, posted disappointing results in its second quarter, leading to a 15% staff reduction and a suspension of dividend payments. The company’s PC client business, a cornerstone of its operations, saw an 8% drop in revenue last year as the overall PC market weakened. Executives are now banking on the introduction of AI features in PCs to spur consumer upgrades.

Titus weighed in on Intel’s position, noting that the PC segment remains vital for the company. “Even with the increased internal pressure, it does not make sense for Intel to lose its most dominant sector in the form of PCs,” Titus explained. He emphasized the importance of innovation in the semiconductor industry, especially as AI markets are poised for significant growth.

“I highly doubt Intel will be ready to sell its AI-focused designs right when the market is about to boom,” Titus added.

This week, Intel launched its Lunar Lake chip, designed to power AI applications, as part of its push to regain a competitive edge. However, Intel outsourced significant portions of the chip’s fabrication to TSMC, a shift from its historical reliance on in-house production.

Qualcomm’s expansion strategy

With the potential acquisition, Qualcomm could significantly expand its footprint in the PC chip market, which is becoming increasingly intertwined with AI-driven computing. Gogia adds that such a deal would “allow Qualcomm to carve out a niche for supporting devices that allow AI tasks to be run without an internet connection.” This could further strengthen Qualcomm’s relationship with Microsoft, especially as both companies continue to explore opportunities in AI PCs.

Qualcomm may also be interested in Intel’s server and HPC segments, opined Neil Shah, VP for Research at Counterpoint Research. “This is a key market where Qualcomm is not yet playing, but where Intel is struggling against NVIDIA and AMD,” he said adding that Intel’s Altera (FPGA) and Movidius (Visual Processing Units) would help fill gaps in Qualcomm’s portfolio.

However, the speculation surrounding this potential acquisition highlights that Intel may still be considering other strategies to cut costs while maintaining its market presence.

“Intel will have to decide which business is long-term lucrative and which is not, especially in a highly competitive environment with both AMD and Arm-based servers gaining ground,” Shah said.

Broader implications

The acquisition, if realized, could also alter competitive dynamics in the semiconductor market. Faisal Kawoosa, Founder and Lead Analyst at Techarc, noted that Qualcomm is well-positioned to capitalize on growth opportunities in the PC sector.

“With Intel’s design capabilities under the belt, Qualcomm can be aggressive about this market and become a strategic partner to Microsoft,” Kawoosa said. He also pointed out that Intel’s core competencies in high-performance processors may be better suited for the server market, where the company could refocus its efforts against the rising dominance of Nvidia in AI and server segments.

Kawoosa added that the acquisition would serve Qualcomm well in a market where “laptops still have huge potential to grow even in markets like India, where penetration is very low.” He said this move could help Qualcomm become a stronger player in the PC and AI sectors.

Oživeno 4. 9. 2024 | Integrovaný překladač ve Firefoxu 130 oficiálně podporuje češtinu a slovenštinu. Ale pozor, do češtiny ani slovenštiny nepřekládá, zatím pouze překládá weby z těchto jazyků. Nově prohlížeč překládá vybrané pasáže i poté, co provedete kompletní překlad stránky. Stačí na stránce ...

Veletrh IFA slaví stoleté výročí a Samsung na něm představil své nejnovější inovace a možnosti, přitom sází na svůj přístup zvaný „AI For All, tedy Umělá inteligence pro každého“. Ukázal zde nejen propojení všech svých produktů, u televizorů předvedl AI vylepšení obrazu i zvuku.

Spreadsheets’ greatest strength — the wealth of data they contain — also makes them nearly indecipherable at a glance. That’s why Microsoft provides numerous ways to filter, format, and highlight data in Excel.

In previous articles, we’ve explained how to use conditional formatting, tables, and PivotTables and PivotCharts to show the most important data in a spreadsheet. In this Excel tutorial, we’ll cover slicers.

What is an Excel slicer?

A slicer is an easy-to-use tool that lets you filter and dynamically change data based on your selected criteria. It’s a great tool for drilling down on information that you want to focus on. Once you’ve set up a slicer in an Excel worksheet, you (or anyone viewing the spreadsheet) can simply click buttons in the slicer to zero in on one or more particular groups of data within the larger data set.

In Excel, both tables and PivotTables include built-in filtering tools, but they can be a little clunky to use. Slicers offer a more user-friendly way to filter data, making them especially useful for spreadsheets you’re sharing with co-workers, executives, or clients.

Where can you use slicers in Excel?

You can apply slicers to any table or PivotTable in Excel. What’s more, you can create multiple slicers for the same table or PivotTable, so anyone viewing the sheet can see which subsets of data you want them to focus on, and then they can click on the slicer buttons to further home in on specific data.

You can also use slicers to filter the data in charts. And if you have more than one PivotTable based on the same data set, you can use the same slicer for all the PivotTables.

In this article, we will walk through how to create and format slicers, use them to filter data, and connect them to multiple PivotTables. We’ll give instructions for Excel for Windows, but the steps are very similar if you’re using Excel in macOS or on the web.

If you want to follow along with the demo, the sample data is below. Simply copy and paste it into a blank Excel file to get started.

YearCategoryProductSales (US Dollars)2019ClothingSocks80,0002018AccessoriesChains50,0002020AccessoriesNecklaces40,0002018EquipmentBasketballs30,0002020EquipmentSoccer Balls20,0002019ClothingPants30,0002018EquipmentFootballs40,0002018AccessoriesRings60,0002019EquipmentSoccer Balls30,0002018ClothingUnderwear30,0002020EquipmentBasketballs50,0002019AccessoriesChains80,0002020ClothingUnderwear25,0002020ClothingSocks30,0002018ClothingHat45,0002018EquipmentSoccer Balls35,0002017ClothingSocks40,0002020AccessoriesRings70,0002019ClothingShirts30,0002018ClothingPants30,000 How to create and format slicers

To begin, highlight the entire table. Then, in the Ribbon toolbar at the top of the screen, select Insert and then Table. On the popup that appears, make sure “My table has headers” is checked and select OK.

Convert the data into table format.

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Convert the data into table format.

Shimon Brathwaite

Convert the data into table format.

Shimon Brathwaite

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Shimon Brathwaite

Now that we have a table, simply click on any cell in the table and then select Insert > Slicer. The popup that appears lets you select which slicers you want to create, with each option corresponding to one of the headers in your table. In this case, select all the checkmarks and click OK.

Check the box next to each slicer you want to create.

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Check the box next to each slicer you want to create.

Shimon Brathwaite

Check the box next to each slicer you want to create.

Shimon Brathwaite

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Shimon Brathwaite

Four slicers appear on the sheet. You can spread them out on the page so they are easier to read.

Drag and drop the slicers so that each is fully visible.

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Drag and drop the slicers so that each is fully visible.

Shimon Brathwaite

Drag and drop the slicers so that each is fully visible.

Shimon Brathwaite

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Shimon Brathwaite

Notice that the buttons within each slicer reflect the data in the table. For instance, there are four different years that appear in various rows in column A. Those four years are represented as buttons in the Year slicer. Likewise, all the categories from column B appear in the Category slicer, and so on.

You can change each slicer’s colors to make it easier to differentiate among them or just for aesthetic reasons. To do so, click one of the slicers, click the Slicer tab on the Ribbon toolbar, and select a new color from gallery that appears. In our example, we’ll click the Category slicer and select the orange color scheme.

You can format slicers using the Slicer tab in the Ribbon toolbar.

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You can format slicers using the Slicer tab in the Ribbon toolbar.

Shimon Brathwaite

You can format slicers using the Slicer tab in the Ribbon toolbar.

Shimon Brathwaite

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Shimon Brathwaite

As a final formatting task, change the colors of the remaining slicers to match the image below:

The table data has been filtered according to our selections, showing 2018 equipment sales only.

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The table data has been filtered according to our selections, showing 2018 equipment sales only.

Shimon Brathwaite

The table data has been filtered according to our selections, showing 2018 equipment sales only.

Shimon Brathwaite

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Shimon Brathwaite

How to filter data with slicers

Now we’ll demonstrate the power of slicers in a table. To begin, let’s filter the table to show only data related to 2018 equipment sales.

To do this, click 2018 in the year slicer. This will deselect 2017, 2019, and 2020, leaving only 2018 selected. Then in the Category slicer, click Equipment to deselect everything except Equipment.

The result? The table now shows only three rows, all of which contain equipment sales from 2018.

The table data has been filtered according to our selections, showing 2018 equipment sales only.

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The table data has been filtered according to our selections, showing 2018 equipment sales only.

Shimon Brathwaite

The table data has been filtered according to our selections, showing 2018 equipment sales only.

Shimon Brathwaite

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Shimon Brathwaite

If you want to show more data in the table, you can select multiple items within a slicer. For example, in the Category slicer, click Clothing, hold down the Ctrl key in Windows or the ⌘ key on a Mac, and then click Equipment. With both of those items selected, our example table now shows all clothing and equipment sales for 2018.

The table now shows clothing and equipment sales from 2018.

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The table now shows clothing and equipment sales from 2018.

Shimon Brathwaite

The table now shows clothing and equipment sales from 2018.

Shimon Brathwaite

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Shimon Brathwaite

When you apply filters to a table, all the original data is still there; it’s just hidden from view. To remove the filters you added, simply click the icon of the red X over a funnel on the top right of each slicer. When you do, all the original data reappears in the table.

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Click the red X icon to remove the filters applied by the slicer.

Shimon Brathwaite

Slicers can also be used to filter the data displayed on charts generated from the same table. To illustrate this, we’ll add a chart to the spreadsheet. Highlight the entire table, go to the Ribbon’s Insert tab, click the pie chart icon, and select the first 2D pie chart in the popup.

Inserting a 2D pie chart based on the table data.

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Inserting a 2D pie chart based on the table data.

Shimon Brathwaite

Inserting a 2D pie chart based on the table data.

Shimon Brathwaite

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Shimon Brathwaite

Now, you will have a pie chart that shows all of the data presented in the table.

With so many data points included, the chart doesn’t look like much of anything.

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With so many data points included, the chart doesn’t look like much of anything.

Shimon Brathwaite

With so many data points included, the chart doesn’t look like much of anything.

Shimon Brathwaite

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Shimon Brathwaite

Not very useful, is it? With so many different items displayed in the chart, the viewer is overwhelmed and can glean no insights from it.

Let’s filter this data using the slicers we created to show just 2020 accessory sales. The result is much easier to understand quickly:

After filtering by the slicers, the chart is much clearer.

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After filtering by the slicers, the chart is much clearer.

Shimon Brathwaite

After filtering by the slicers, the chart is much clearer.

Shimon Brathwaite

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Shimon Brathwaite

To delete the chart, right-click it and select Cut.

If you want to remove any slicer from your spreadsheet, first clear the filters on your slicers to restore the table back to normal. Then delete the slicers by right-clicking each one and selecting the Remove option.

Removing a slicer

Shimon Brathwaite

Remove all the slicers, leaving only the table you created initially.

How to use slicers with PivotTables

In addition to using slicers on regular tables, you can also use them on PivotTables. To begin, highlight your table of data, go to Insert in the Ribbon toolbar, and select PivotTable. Select OK on the popup.

Create a PivotTable based on the table data.

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Create a PivotTable based on the table data.

Shimon Brathwaite

Create a PivotTable based on the table data.

Shimon Brathwaite

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Shimon Brathwaite

You will be directed to a new page with a blank PivotTable on the left and a PivotTable Fields sidebar on the right. To populate the information, first check the checkbox next to Sales (US Dollars) in the sidebar. This places it in the Values area at the lower right. Next, drag the Year item down to the columns area in the sidebar. Then drag Category and Product down to the Rows area — place Category first and Product second.

Building a PivotTable using the sidebar. (Click image to enlarge it.)

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Building a PivotTable using the sidebar. (Click image to enlarge it.)

Shimon Brathwaite

Building a PivotTable using the sidebar. (Click image to enlarge it.)

Shimon Brathwaite

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Shimon Brathwaite

These actions populate the PivotTable on the left. The sales data is grouped first by category, then by product, with each year’s data appearing in a separate column. (For more details about working with PivotTables, see our PivotTables tutorial.)

Now follow the same steps as before to add a slicer to this PivotTable. Click anywhere on the table, go to the Insert tab and select Slicer. Check all the checkboxes and select OK.

Four slicers appear on the sheet. You can now use the slicers to filter the data in the PivotTable just as you did the data in the regular table earlier.

Using the Category slicer to filter the PivotTable so it shows only clothing sales.

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Using the Category slicer to filter the PivotTable so it shows only clothing sales.

Shimon Brathwaite

Using the Category slicer to filter the PivotTable so it shows only clothing sales.

Shimon Brathwaite

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Shimon Brathwaite

As always, you can click the X icon at the upper right of the slicer to remove its filtering.

How to use slicers across multiple PivotTables

Now, there is a unique feature that can be used when you have two or more PivotTables in an Excel workbook. Slicers can be used across multiple PivotTables as long as they are based on the same data set.

So let’s try this: return to your original worksheet, create a second PivotTable, and populate the data. In the real world, you likely wouldn’t want to create a second PivotTable that’s identical to the first one; PivotTables are generally used to focus on particular subsets of data. So when you create the second PivotTable for our demo, check the Sales (US Dollars) checkbox, then drag Category and Year to the Rows area.

Our second PivotTable. (Click image to enlarge it.)

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Our second PivotTable. (Click image to enlarge it.)

Shimon Brathwaite

Our second PivotTable. (Click image to enlarge it.)

Shimon Brathwaite

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Shimon Brathwaite

Then, return to the first PivotTable you created, which already has slicers. Select the Year slicer, navigate to the Slicer tab in the Ribbon, and select Report Connections. (Alternatively, you can right-click the Year slicer and select Report Connections from the menu.) In the popup that appears, check the checkmark next to the second PivotTable you created and hit OK.

Connecting a slicer to the second PivotTable.

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Connecting a slicer to the second PivotTable.

Shimon Brathwaite

Connecting a slicer to the second PivotTable.

Shimon Brathwaite

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Shimon Brathwaite

Now, any change that you make with the slicer in the first sheet will be transferred to the other sheet as well. Try it out by changing the Year slicer to include only 2018.

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The connected PivotTable is now filtered for 2018 only.

Shimon Brathwaite

In this way, you can have multiple sheets with different views and data visualizations that dynamically change and remain in sync with one another.

If you ever need to disconnect a slicer, simply select that slicer, open the Report Connections dialog box, and deselect the PivotTable that you want to disconnect.

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Disconnecting a PivotTable from a slicer.

Shimon Brathwaite

And that’s all you need to know to get started with slicers. Time to start slicing your data!

Further reading:

• Excel basics: Get started with tables
• How to use PivotTables and PivotCharts in Excel
• How (and why) to use conditional formatting in Excel
• Microsoft cheat sheets: Dive in Windows and Office apps

Rodinný rodokmen – strom předků – se dá dnes sestavit mnohem snadněji než dřív. Staré matriční knihy, za kterými badatelé dřív museli do archivů, jsou totiž online na internetu.

The 2024 State of the vCISO Report continues Cynomi’s tradition of examining the growing popularity of virtual Chief Information Security Officer (vCISO) services. According to the independent survey, the demand for these services is increasing, with both providers and clients reaping the rewards. The upward trend is set to continue, with even faster growth expected in the future. However,

The 2024 State of the vCISO Report continues Cynomi’s tradition of examining the growing popularity of virtual Chief Information Security Officer (vCISO) services. According to the independent survey, the demand for these services is increasing, with both providers and clients reaping the rewards. The upward trend is set to continue, with even faster growth expected in the future. However, The Hacker Newshttp://www.blogger.com/profile/[email protected]

Qualcomm is allegedly sniffing at the beleaguered remains of Intel and may try to acquire parts of the company. Will Apple make its own counterproposal?

Apple’s decision to abandon its processors in favor of Apple Silicon reflected a wider malaise. Try as it might, Intel found itself unable to accelerate processor development to the same extent as Apple found it could with ARM-based Apple Silicon chips, and what began as a jubilant relationship expired. Intel had saved Apple from the PowerPC chip disaster but couldn’t keep the pace with modern mobile processors.

The rest, as they say, is history.

Intel shudders, Qualcomm ascends

Qualcomm, meanwhile, knows a good idea when it sees one and has been dancing in Apple’s shadow with its own move to manufacture ARM-based processors. Those fast chips are picking up vendor sales at Intel’s expense. 

But it seems Qualcomm wants to take things a step further, which is why it has been exploring the possibility of acquiring parts of Intel’s design business, particularly the PC design business. 

A deal has not been reached — Reuters tells us Intel says it is “deeply committed” to its PC business — and Qualcomm hasn’t approached Intel to discuss its plans. In other words, all or none of this could be true.

The Apple connection

In context, Intel is encountering tough headwinds, prompting deep layoffs and a pause in dividend payments. The company’s PC client business declined 8% last year, reflecting weak PC sales across the board.

Apple’s Mac sales kicked against this trend, increasing 20.8% year on year in Q2 against a PC industry average 3% growth — mostly attributable to Apple’s extra million Mac sales.

With Apple expected to introduce incredibly performant M4 Macs this side of Christmas, all of which will be capable of running Apple Intelligence with built-in AI support, Cupertino is counting on its PC sales growth to continue. The company is unique in that it offers a completely compatible range of AI-supporting products in every key form factor (Mac, tablet, smartphone). No one else has this.

Qualcomm competes

Qualcomm wants a slice of that market, too. Its newly introduced Snapdragon processors are winning praise across the PC media for their low power use and high performance (though these still lag behind Apple Silicon in many respects).

All the same, as a business it may well have learned from Apple’s integrated approach to product design. A strategic Intel acquisition would give it an opportunity to begin building its own platform ecosystem, or at least make additional cash through hardware sales on its own account. Though it must be noted that most PCs capable of running AI cost more than some of Apple’s systems (e.g., the Mac mini) that are also capable of doing so.

The myth that PCs are cheaper is an enduring one, but you get what you pay for, and Crowdstrike showed us the risks of that platform.

But why wouldn’t Qualcomm want to grab a larger slice of the PC industry pie?

More than a modem

There is a clear competitive relationship between Apple and Qualcomm. Not so long ago, Apple settled outstanding litigation between the two companies in order to begin using Qualcomm’s 5G chips in its devices. The iPhone manufacturer had hoped to build its own 5G modems with the help of Intel, but that plan didn’t bear fruit.

In the end, Apple acquired Intel’s modem design unit and a big bucket full of related mobile patents for a billion dollars. It’s fair to say modem development has proved a struggle, but Apple is now expected to introduce its first 5G modems as soon as 2025. 

When it does, Apple will no longer be dependent on Qualcomm.

But, given that Qualcomm has its own chip design talent, will Apple want it to emerge as a hardware competitor? What is the risk that some key patents used by Apple may suddenly migrate from Intel to Qualcomm if such a deal does take place? After all, one of the key disputes between both firms has been around patent licensing costs.

All of this is speculation, of course: Qualcomm may never bid for Intel’s PC business. But if it does, and if Apple doesn’t like it, then it may be instructional to note that Qualcomm’s market cap currently stands at $182 billion, in contrast to Intel’s $82.7 billion and Apple’s eye-watering $3.38 trillion.

That difference in financial capital hints at what could be a dramatic bidding war, but almost certainly suggests regulatory investigation whoever seals the deal, if such an event happens at all. 

Please follow me on LinkedIn, Mastodon, or join me in the AppleHolic’s bar & grill group on MeWe.

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