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Modern cybersecurity professionals require advanced technologies to deter, detect and expel hackers, and the predictive benefits of AI can mean the difference between data protection and ruin.
The average cost of a data breach in the U.S. hit a high-water mark of $9.48 million in 2023. Losses have ticked up every year since 2013, even during the global health emergency of Covid-19 when many businesses shuttered. An analysis in IBM’s 2024 data breach report indicates that organizations that employed extensive AI security automation saved $2.22 million, while also lowering cybersecurity insurance.
Industry leaders would be well-served to think about cyberattacks outside the financial implications, as well. Should your organization pay a ransomware demand or right the ship after a crushing malware attack, the reputational damage can far outweigh the dollars. When hackers steal confidential, sensitive and personal identity information, those in your orbit are negatively impacted. Employees, customers and industry partners may file civil actions.
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And, when word gets out that your enterprise cannot protect personal data, business can get eerily quiet. It’s not uncommon for an institution to file for bankruptcy within one year of a significant breach of trust. Fortunately, AI cybersecurity can harden your defenses and make cybercriminals look elsewhere for low-hanging fruit.
What role does AI play in cybersecurity?
There are wide-reaching benefits to integrating AI into an operation’s cybersecurity posture. The lengthy list, which we’ll briefly cover here, does have one central theme — reaction time. The bedrock of the thought leadership behind using AI in the data protection sector involves reducing how long it would otherwise take to detect and expel hackers.
The role AI plays in today’s lightning-quick hacking landscape can determine whether companies suffer stinging losses and hiccups or walk away unscathed. When you consider how fast a sophisticated cybercriminal can work, it’s abundantly clear why time is on the bad guys’ side unless we do something about it.
Ransomware attacks: These hacks usually take 4 hours, but advanced persistent threats can take over a business network in 45 minutes. Ransomware attacks occur every 11 seconds.
Phishing emails: Almost 30% of all phishing emails are opened by their recipients. These malware-laced communications account for 91% of all cyberattacks.
Malware deployment: Hackers deploy malware at a rate of 11.5 attacks per minute.
The average hacker needs only 9.5 hours to pilfer off valuable and sensitive digital assets. Cybercriminals can operate with impunity if no one is monitoring activity while the business is closed and staff are fast asleep. Operations without AI, machine learning (ML) and other advanced technologies typically average 197 days to notice a breach and another 67 days to contain it. Hackers are more than happy to hide in plain sight and copy incoming data until you expel them.
The benefits of using predictive AI technology
The fundamental element of AI in cybersecurity may be its time management effectiveness. It’s important to understand how this forward-looking technology benefits an organization’s overall cyber hygiene. Here are some ways AI delivers quantitative and qualitative data security benefits.
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Advanced threat detection
The ability of AI to sift through massive amounts of data seemingly at light speed cannot be matched by human beings. Programmed to learn and identify even subtle anomalies in network traffic, user activity and system logs can make it difficult for hackers to go undetected. Generating a real-time and ongoing analysis of wide-reaching movement, anything that deviates from predictive patterns gets flagged. A cybercriminal or deployed malicious software triggers an immediate threat detection alert. The most skilled perpetrator could not get the 45 minutes needed to effectively insert a ransomware file.
Behavioral analytics
To say that AI exceeds expectations in terms of behavioral analytics would be something of an understatement. ML, largely a sub-category of AI, involves following and understanding consistent patterns. For example, a legitimate network user enters a username, password, then a two-factor authentication code. Once inside the system, staff members carry out relatively consistent tasks. That means they open the same programs, access similar data and perform these duties in a uniform manner.
When a hacker orchestrates an attack, the digital burglar isn’t interested in filing incident reports or tabulating inventory. Cybercriminals head for valuable and confidential information that can be sold on the dark web. Because AI and ML follow the behaviors of users — sometimes down to keyboard strokes — alarms are triggered, and prompt actions are taken to confine and expel the threat.
Reduce fault threat alerst
Before organizations started adopting AI and ML, responding to false alarms seemed like the cost of doing business. That’s largely because the alternative was not knowing when a genuine threat was in progress. In terms of efficiency, pre-AI threat detection was a lot like a fire department responding to dozens of alarms being set off by overly sensitive heat detectors.
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The rise of AI has been a game changer in terms of decreasing false alarms and reducing the time managed IT and security officers spend vetting each and every one. As technology adapts to common false positives and learns to distinguish between low-level and heightened irregularities, cybersecurity professionals spend fewer wasted hours.
Non-stop threat monitoring and learning
Although people and most machines require downtime, AI works relentlessly to identify abnormalities. During this never-ending process, technology continues to accumulate actionable information. It can adapt to changes in the digital landscape and be reconfigured to assess new norms. The alternative to AI would be hiring a full-time staff and checking systems activities 24 hours a day, 7 days a week. For many organizations, the cost of non-stop threat monitoring can prove prohibitive.
Getting comfortable with AI automated incident response
One of the processes that AI delivers involves automated threat responses. Not every business director feels comfortable allowing technology to push back on threats, be they malware, ransomware or a human attempting a blunt-force attack. There’s a certain loss of control that accompanies letting the so-called “machines take over.” But automated incident responses may actually be in your best interest.
Industry leaders can choose their comfort level regarding which threats are handled by the technology and which get elevated for a real person’s attention. Low-level threats are typically managed by AI, and it’s commonplace to have AI start the threat containment efforts while security professionals respond to an alert. These rank among the benefits companies gain from automating varying incident responses.
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Speed and efficiency: Pre-determined responses to emerging threats happen immediately. The speed at which AI can address these issues helps efficiently mitigate risk.
Minimize human error: The majority of successful data breaches can be traced back to human error. Technologies such as AI and others carry out the procedures and duties assigned to them. You can’t trick AI into allowing users to access data deemed off-limits.
Integrating AI and ML may be one of the most cost-effective ways to harden your cybersecurity position. It does the work of dozens of humans faster and more efficiently without logging overtime hours. Adaptable to wide-reaching networks and architectures such as zero trust, its ability to sift through massive amounts of data, identify patterns and constantly learn makes it invaluable in risk management. When a threat actor finds a way into your network or an insider attempts to steal a trade secret, they cannot escape AI’s watchful eye.
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The Pixel 9 Pro XL is the most premium model in Google’s latest smartphone lineup. There’s also the Pixel 9 Pro Fold, but foldable devices have their own category. Pixel 9 series buyers have already been able to enjoy all the new features and improvements for a few weeks. However, a Pixel 9 Pro XL owner had a difficult time due to a problem with the device’s rear camera bar.
There could be a problem with the Pixel 9 Pro XL’s camera bar
A Google Pixel 9 Pro XL user reported on Reddit that the phone’s rear camera bar just came off, for no apparent reason. According to the post, the device had not suffered any rough use or drops that could cause the problem. The user first noticed the issue when the Pixel 9 Pro XL’s camera glass became fogged up internally. After removing the protective case, the user noticed that there was a gap between the camera bar and the body of the phone. Then, a light tug was enough for the piece to fall.
Currently, there’s only one report about the problem, so it could be a case of defective unit. It is normal for there to be a small percentage of defective units in production batches of new tech products. However, it is still a frustrating situation for those who have to deal with it.
Google revamped the design of the camera module on the Pixel 9 series
Since the Pixel 6 series, Google has used a bar-shaped camera module design. The edges of the bar meet the sides of the device in a curve. However, this year, the company decided to change the design slightly. The Pixel 9 series retains the module placement and horizontal distribution of sensors, but the bar adopts an elongated pill shape. The new design implies that the edges of the module are no longer “fused” to the sides of the phone.
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The new design could be the source of the problem, although there’s no confirmation on that yet. Now that the camera module doesn’t blend with the sides of the phone, Google needs to make sure it’s well integrated with the rear area in other ways. Remember, the Pixel 9 series boasts an IP68 rating, so the build must be solid.
Fortunately, the affected user was able to obtain a replacement unit through their warranty. However, their post expresses concern about the possibility of facing the problem again. Let’s hope that’s not the case.
2K and developer 31st Union just unveiled Project: Ethos, a free-to-play 3rd-person hero shooter. It’s entering a crowded and fraught marketplace, but the publisher says this is an “exciting evolution” of the genre.
That evolution seems to take the form of some light roguelike mechanics. The playable characters evolve throughout each match, via semi-randomized upgrades unique to each hero. The publisher gives an example of evolving a sniper into a “close-range skirmisher” or a “support role into a powerful lone wolf.”
The “abilities, stakes and challenges” change from match to match and players can eventually unlock powerful Augments to further enhance runs. It remains to be seen if these mechanics can set it apart from the pack, but you can find that out for yourself. There’s a community playtest .
Players can test out the game’s signature Trials mode, which is an “ongoing, persistent fight” or check out the Gauntlet. This is your standard head-to-head tournament mode, with teams and brackets.
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This community playtest goes until October 20 in the US, Canada, Mexico and much of Europe. There is a fairly annoying hurdle to jump through to access the early build. You have to complete a Twitch Drop and stream 30 minutes of content from . There’s no information yet regarding an actual release date for people who don’t want to sit through a 30-minute stream.
AI search engine Perplexity is in fundraising talks and hopes to raise around $500 million at an $8 billion valuation, according to the Wall Street Journal.
If a deal happens with those terms, it would more than double Perplexity’s valuation from its $3 billion valuation when it raised from SoftBank over the summer. The WSJ reports that the company currently receives about 15 million queries a day and brings in around $50 million in annualized revenue.
Perplexity uses AI to help people search the web in a chatbot-style interface. Some news publishers have accused the company of unauthorized web scraping and plagiarism, and The New York Times has even sent Perplexity a cease-and-desist letter, but CEO Aravind Srinivas said he wants to work with publishers and has “no interest in being anyone’s antagonist here.”
These fundraising talks come after OpenAI announced raising a $6.6 billion round at a $157 billion valuation. While products like OpenAI’s ChatGPT have blurred the line between chatbot and search engine, the company is moving more directly into search with SearchGPT.
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Perplexity did not immediately respond to a TechCrunch request for comment.
It’s dispiriting to see that even after being made aware of the breach 2 weeks ago, IA has still not done the due diligence of rotating many of the API keys that were exposed in their gitlab secrets.
As demonstrated by this message, this includes a Zendesk token with perms to access 800K+ support tickets sent to info@archive.org since 2018.
Whether you were trying to ask a general question, or requesting the removal of your site from the Wayback Machine—your data is now in the hands of some random guy. If not me, it’d be someone else.
Here’s hoping that they’ll get their shit together now.
One of the constants in computing is the need for more storage. While 8TB SSDs offer both speed and capacity, they can be a little pricey, although there are deals available if you’re prepared to shop around. If you need more storage – nearly double, in fact – purchasing a 15.36TB SSD often provides better value on a per-terabyte basis.
For example, the Intel D5-P5316 2.5-inch 15.36TB SSD is available on Amazonfor $1,650. It boasts write speeds of 3200 MB/s and read rates of 7000 MB/s. If you’re after a cheaper option, the Kioxia CD6-R KCD6XLUL15T3 is priced at a more affordable $1,397.63 on ServerPartDeals. This model offers 4000 MB/s write speeds and 5500 MB/s read rates.
In contrast, Samsung‘s 8TB 870 QVO SATA III SSD usually sells for $849.99 on Amazon, although it’s currently selling for $639.95. On a per-terabyte basis, the Samsung SSD works out to $106 at its usual price, and $80 at its sale price. The double-capacity Intel and Kioxia models cost $107 and $91 per terabyte, respectively.
The catch
However, as is often the case, there’s a catch.
The Intel and Kioxia drives, like other 15.36TB models, use the U.3 interface, which is specifically designed for enterprise environments rather than the more common M.2 format seen in consumer devices. These drives require a system with U.3 NVMe functionality, meaning they cannot be used in standard consumer desktops or laptops, making them less accessible to the average user without the proper setup.
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Despite this, their impressive performance metrics and price per terabyte make them appealing options for professional and enterprise-level storage needs. If you’re looking to save even more, shopping around and exploring platforms like eBay can sometimes yield even better deals.
At the time of writing, we found the Kioxia CD6-R KCD6XLUL15T3 listed on the auction site for $1,185, which works out to a bargain $77.15 per terabyte – a price that’s hard to ignore.
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Apple’s MacBook Air M3 represents the latest of the company’s very successful thin-and-light laptops built around Apple Silicon’s fast and highly efficient chipsets. It’s one of the best laptops made, and Windows machines have had a hard time keeping up.
Now, Intel has introduced a new chipset, the Core Ultra Series 2, also know as Lunar Lake, that aims to rectify things with much better efficiency. The Asus Zenbook S 14 is one of the first laptops introduced with the new chipset. Can it compete?
2 x USB-C with Thunderbolt 4 1 x USB-A 3.2 Gen 2 1 x HDMI 2.1 1 x 3.5mm headphone jack
2 x USB-C with Thunderbolt 4 1 x 3.5mm audio jack 1 x MagSafe 3
Touch
Yes
No
Wireless
Wi-Fi 7 Bluetooth 5.4
Wi-Fi 6E Bluetooth 5.3
Webcam
1080p with infrared camera for Windows 11 Hello
1080p
Battery
72 watt-hour
52.6 watt-hours
Operating system
Windows 11
macOS Sonoma
Price
$1,399+
$1,099+
Rating
4 out of 5 stars
4 out of 5 stars
There aren’t many configurations of the Zenbook S 14 available yet. Our review unit costs $1,500 with an Intel Core Ultra 7 258V chipset, 32GB of RAM, a 1TB SSD, and a 14-inch 2.8K OLED display.
The MacBook Air M3 has several options. The base model costs $1,099 with an 8-core CPU/8-core GPU M3 chipset, 8GB of RAM, a 256GB, and a 13.6-inch 2560 x 1664 IPS display. RAM and storage upgrades include $200 to upgrade to 16GB or 512GB, and $400 to go to 24GB and 1TB. An upgrade to 2TB is a whopping $800. Our review unit cost $1,699 for an 8-core CPU/10-core GPU M3, 16GB of RAM, and a 1TB SSD. The high-end configuration with 24GB of RAM and a 2TB SSD is $2,299.
So, when configured similarly, the MacBook Air M3 is $100 more. That makes them close enough that other factors will weigh more.
The MacBook Air M3 is an incredibly thin laptop while still maintaining Apple’s usual excellent build quality and solid chassis. It’s CNC machined out of a single chunk of aluminum, and it’s an elegant aesthetic in one of four colors. The Zenbook S 14 is a pretty thin laptop as well, and it uses a “ceraluminum” (Asus’ word) material to be very light and yet sturdy. It’s a good-looking laptop as well, coming in either dark gray or white and with a geometric pattern on the lid.
Both laptops have the usual quality hinge that opens with one hand, and while the MacBook Air feels dense and cold in hand, the Zenbook has a warm texture. The bottom line is that nobody is likely to buy either laptop based solely on their look and feel.
The Zenbook S 14 has the very good Asus keyboard that you’ll find on the entire ZenBook line. It has plenty of spacing and large keycaps, as well as light and snappy switches. The MacBook Air uses Apple’s excellent Magic Keyboard, which is my favorite. It has a perfect layout, comfortable keys, and the most precise switches on a laptop today. The Zenbook’s mechanical touchpad feels Ok, but it’s almost too large, leaving a very small palm rest. The MacBook Air’s Force Touch haptic touchpad is perfectly sized and works great, with the Force Click function that adds additional features with a firmer “click.” The keyboard and touchpad are Apple strengths.
Connectivity favors the Zenbook S 14, which has a couple of legacy ports to go with the same two Thunderbolt 4 connections. And it has more up-to-date wireless connectivity. Both laptops have 1080p webcams, and the Zenbook uses an infrared camera with Windows 11 facial recognition compared to the MacBook Air’s Touch ID fingerprint reader. The Zenbook supports Studio Effects software that enhances videoconferencing.
Intel’s Lunar Lake chipsets are aimed at competing directly with Apple Silicon. We reviewed the Zenbook S 14 with the Core Ultra 7 258V, a 17-watt, 8-core (four Performance and four Low Power Efficient), 8-thread chipset. It uses the newest Intel Arc 140V integrated graphics. The MacBook Air uses Apple’s M3 chipset with eight CPU cores and eight or 10 GPU cores. We reviewed the faster version.
In our benchmarks, the MacBook Air M3 was faster in all but the Handbrake test. It was faster in both single-core and multi-core tests. And its GPU was more than twice as fast in the 3DMark Wild Life Extreme benchmark.
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It’s not that the Zenbook S 14 is a slow laptop. It’s just that the MacBook Air M3 is meaningfully faster.
Geekbench 6 (single/multi)
Cinebench R24 (single/multi/battery)
Handbrake
3DMark Wild Life Extreme
Asus Zenbook S 14 (Core Ultra 7 258V / Intel Arc 140V)
The Zenbook S 14 uses a 14-inch 2.8K OLED display running at up to 120Hz. It’s a lovely display with OLED’s usual bright, dynamic colors and inky blacks. That compares to the MacBook Air’s 13.6-inch 2560 x 1664 IPS display running at 60Hz.
While the MacBook Air’s display is a very good example of IPS technology, and it’s very bright and reasonably colorful, the Zenbook’s OLED panel has much wider colors and near-perfect blacks. Our review unit had oddly poor color accuracy, but that’s unusual and likely an outlier. The Zenbook’s display will be appreciated by creators and media consumers.
The MacBook Air is the thinnest laptop you can buy, and the Zenbook S 14 is only a little thicker. In spite of having a larger display, the Zenbook is around the same width and depth, and it weighs about the same. These are both very portably laptops.
When it comes to battery life, the Zenbook S 14 comes about as close to the MacBook Air M3 as any recent Windows laptop has managed. It’s only three hours behind in our web-browsing test and an hour behind in our video-looping test. And the two laptops managed about the same in the demanding Cinebench R24 multi-core test.
Web
Video
Cinebench R24
Asus Zenbook S 14 (Core Ultra 7 258V / Intel Arc 140V)
These are both great laptops. The Zenbook S 14 leverages the Intel Lunar Lake chipset for great battery life, which is an early win for the platform. It’s a nicely designed and built laptop, and it really doesn’t have any significant flaws.
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The MacBook Air is also close to perfect, and it’s meaningfully faster with slightly better battery life. It has a much better keyboard and touchpad, and generally a very elegant design. It’s a bit more expensive, but worth it — although if you must have Windows, then the Zenbook S 14 is a great choice.
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