Following its recent release, Apple’s latest macOS update, dubbed Sequoia (macOS 15), has disrupted the functionality of several widely used cybersecurity tools, including those from CrowdStrike, SentinelOne, and Microsoft.

Users and developers have voiced frustrations on social media and in Mac-focused forums about issues leaving many security applications non-operational. Reports highlight problems with tools like CrowdStrike, SentinelOne, Microsoft Defender, and ESET, alongside browser issues, particularly with Firefox, where the OS firewall sometimes blocks web access. The root cause is unclear, but the disruptions are creating significant challenges for both end-users and enterprise security teams.

The key issue seems to stem from changes Apple has made in Sequoia’s network stack, which cybersecurity firms say is interfering with their products. For example, CrowdStrike delayed support for Sequoia, citing complications in adapting their software. Similarly, SentinelOne warned users not to upgrade without ensuring proper support, while Microsoft’s Defender and ESET have faced similar difficulties. Despite SentinelOne and ESET eventually providing compatibility, significant disruption remains across the community.

Apple has yet to comment, leaving security firms and users to manage the situation. CrowdStrike is awaiting a Sequoia update to offer full support, while temporary workarounds are being shared to address issues like firewall settings and basic web browsing. For now, it may be advisable to delay upgrading to macOS Sequoia until Apple or security providers release compatible updates.

Google has announced that users can now securely sync passkeys across all devices, not just Android, making sign-ins faster and more secure.

Passkeys use biometrics, such as your fingerprint, face, or screen lock, to sign in to apps and websites, thereby making it easier and more secure than using traditional passwords. Whereas previously, only Android devices could save passkeys, requiring a QR code scan for use elsewhere, Google’s latest update means users can now save passkeys to Google Password Manager on desktops (Windows, macOS, and Linux), with ChromeOS in Beta.

Once a passkey is saved, it syncs automatically across devices. Google has also introduced a Google Password Manager PIN for extra security, ensuring passkeys are encrypted and inaccessible to others, even Google.

To start using use passkeys on a new device, users will need their Google Password Manager PIN or Android screen lock. Users can set up a six-digit recovery PIN by default or select “PIN options” to create a longer alpha-numeric PIN.

Google says that with passkeys available for sites like Google, Amazon, and PayPal, and with Google Password Manager built into Chrome and Android, users can start benefitting from this secure, more convenient change without the need for extra apps.

Engineers at the Massachusetts Institute of Technology (MIT) are developing a new kind of reconfigurable masonry made from 3D-printed, recycled glass.

Fits Together Like LEGO 

MIT says the new multilayered glass bricks, each in the shape of a figure-of-eight, are designed to interlock, much like LEGO bricks.

3D Printed 

One of the big advantages of the new glass bricks is that they are made using a custom 3D glass printing technology (provided by MIT spinoff Evenline). The inspiration for using glass and the brick’s shape came partly from when 2 of the engineers, Kaitlyn Becker, and Michael Stern, were still undergraduates and learned the art and science of blowing glass in MIT’s Glass Lab.

It was this experience that led Stern to design a 3D printer capable of printing molten recycled glass.

Tested 

Becker and Stern collaborated to test whether 3D-printed glass could function as structural masonry units comparable to traditional bricks. Using the latest version of Evenline’s Glass 3D Printer (G3DP3), which melts recycled glass bottles into a printable form, they produced prototype bricks from soda-lime glass. The figure-eight design bricks featured two round pegs, similar to LEGO studs, allowing them to interlock and form larger structures. A removable material between bricks prevented scratches, enabling easy dismantling and recycling.

Strong 

The MIT team tested the glass bricks’ strength using an industrial hydraulic press and found that the strongest bricks could withstand pressures similar to concrete blocks. These bricks were primarily made of printed glass, with a separately manufactured interlocking feature, suggesting that most of the brick can be printed from glass, while the interlocking part can be made from various materials.

The Advantages 

The many advantages of the 3D-printed glass brick system include:

– Sustainability. The bricks are made from recycled glass, supporting circular construction by reusing materials and reducing the need for new manufacturing, which lowers the construction industry’s embodied carbon.

– Reusability. The bricks can be disassembled and reassembled multiple times for different structures, extending their lifespan across generations of buildings.

– Recyclability. Glass is highly recyclable. For example, the glass used by MIT’s 3D printer comes primarily from recycled glass bottles in the first place which are crushed, melted in a furnace, and then transformed into a molten, printable material used in the 3D glass printer. Also, once the glass bricks have been made, they can be remelted again and reshaped without contamination, allowing bricks to be recycled into new forms. As Kaitlyn Becker, assistant professor of mechanical engineering at MIT says: “We’re taking glass and turning it into masonry that, at the end of a structure’s life, can be disassembled and reassembled into a new structure, or can be stuck back into the printer and turned into a completely different shape. All this builds into our idea of a sustainable, circular building material.” Becker also highlights how, “As long as it’s not contaminated, you can recycle glass almost infinitely”.

– Strength. As highlighted in MIT’s mechanical tests, the glass bricks can withstand pressures similar to concrete, making them viable for structural use.

– Their interlocking design. Like LEGO, the bricks feature interlocking pegs, enabling easy assembly, and creating strong, self-supporting structures.

– Scratch and crack prevention. A removable material between bricks prevents damage during assembly and dismantling.

– Adaptability. The figure-of-eight design allows for curved wall constructions and offers flexibility in design. This allows for more creative and varied structural forms, making it possible to create aesthetically unique and functional buildings that traditional brick designs may not easily support.

– The potential for scalability. The system can be scaled up to create larger structures, with potential for various configurations and reconfigurations. As Stern says: “We have more understanding of what the material’s limits are, and how to scale,” and that “We’re thinking of stepping stones to buildings, and want to start with something like a pavilion – a temporary structure that humans can interact with, and that you could then reconfigure into a second design.” 

– The environmental benefit of minimising the manufacturing of new materials and reducing the construction industry’s “embodied carbon”, i.e. the greenhouse gas emissions associated with every process throughout a building’s construction, from manufacturing to demolition.

Drawbacks? 

Although the system is still at the development stage and the engineers have been keen to highlight the advantages of the system, it is possible to think of some of the more obvious potential disadvantages, such as:

– Producing glass bricks using 3D printing requires specialised equipment and processes, which might be more expensive and complex than traditional brickmaking.

– Glass typically has poor insulating properties, so structures made from glass bricks may not retain heat as effectively as those built with traditional materials.

– The need for a separate interlocking feature made from a different material could complicate the production and assembly process, reducing the system’s simplicity and uniformity.

– Widespread use of glass bricks might face resistance due to unfamiliarity or scepticism about their long-term durability and safety in construction. Also, the unusual shape and the fact that it’s a new material may require training, e.g. for builders.

Glass Already Being Used To Make Bricks 

Although the 3D printer idea for full glass bricks is new, it’s worth noting here that recycled glass is already being experimented with in similar ways for use in construction projects. For example, researchers at Nanyang Technological University (NTU) in Singapore have developed a concrete mix using recycled glass as a substitute for sand, which is increasingly scarce due to overuse. This glass-based concrete has been successfully used in 3D printing to create a 40 cm-tall concrete bench, demonstrating its viability for load-bearing construction applications.

What Does This Mean For Your Organisation? 

The development of 3D-printed glass bricks at MIT presents a promising and bold vision for sustainable construction, combining innovation in design and environmental responsibility. By reimagining glass as a structural material and leveraging 3D printing technology, these interlocking bricks could offer a versatile solution that embraces circular construction principles. As the building industry seeks to reduce its environmental impact, these bricks present a potential alternative by utilising recycled glass, minimising waste, and allowing structures to be easily reconfigured and recycled at the end of their lifespan.

While challenges remain, such as higher production costs and concerns about insulation and durability, the adaptability and recyclability of the glass bricks highlight their potential.  As with any new material and system though, acceptance and implementation are likely to take time, something that we’re running out of when it comes to decarbonising industries.

However, looking on the bright side, the demonstrated strength of the bricks, combined with their aesthetic and sustainable benefits, points towards a future where glass could play a significant role in eco-friendly construction. The success of this system could even pave the way for further exploration of recycled materials in 3D printing, and with continued innovation, it’s possible to see how these glass bricks and/or concrete using crushed up glass instead of sand, could become a cornerstone in the move towards more sustainable building practices.

This video tutorial explains in depth how to use ChatGPT to optimise your LinkedIn profile.

[Note – To Watch This Video without glitches/interruptions, It’s best to download it first]

The Magnifier tool allows you to zoom in on any part of your screen, which is especially useful when working with small text or detailed images during presentations or document reviews. Here’s how it works:

Enable Magnifier

– Press Win + Plus (+) to activate the Magnifier.

Adjust Zoom Levels

– Use Win + Plus (+) to zoom in and Win + Minus (-) to zoom out.

Exit Magnifier

– Press Win + Esc to turn off Magnifier.

ChatGPT’s maker, OpenAI, has announced the introduction of its new OpenAI o1 large language model that can use “complex reasoning” to fact-check its own answers before giving them.

ChatGPT Plus and Teams Users Can Try It Now 

The new o1 model is already available to ChatGPT Plus or Team users, and in OpenAI’s API. OpenAI o1 is a series of AI models, currently comprising of a ‘Preview’ version, which Open says uses “advanced reasoning”, or the o1-mini (lighter version), which OpenAI says is “Faster at reasoning” (than its other models), and is particularly good for coding tasks.

What’s So Different About o1? 

What sets OpenAI o1 apart from other models is its enhanced reasoning capabilities, designed to tackle complex, multi-step problems with a thoughtful, more holistic approach. Unlike previous models like GPT-4 (which focus on speed), o1 takes more time to “think through” problems, improving its performance on tasks requiring deeper analysis, such as advanced coding, mathematical reasoning, and document comparison. OpenAI says this is because o1 has been “trained with reinforcement learning to perform complex reasoning. o1 thinks before it answers – it can produce a long internal chain of thought before responding to the user”. 

OpenAI says it’s the reinforcement learning (train-time compute) and the extra time ‘thinking’ (test-time compute) that significantly reduces hallucinations. In other words, it is sacrificing speed in favour of accuracy and depth , enabling o1 to excel at complex problem-solving. This should make o1 ideal for use cases where precision is more critical than quick responses. ChatGPT users may argue, however, that precision, i.e. real (not ‘made-up’ answers) has always been completely necessary.

Chain-of-Thought Approach 

OpenAI says the fact that o1 uses a chain-of-thought when attempting to solve a problem, thinking for a long time before responding to a difficult question as humans do, is a large part of the secret of its apparent success. The fact that o1 breaks down “tricky steps into simpler ones” and “learns to try a different approach when the current one isn’t working” is credited with being the process that “dramatically improves the model’s ability to reason”. 

Just How Good Is It? 

OpenAI says that to highlight the reasoning improvement over GPT-4o, it tested the o1 models on a diverse set of human exams and ML benchmarks. For example, to test o1 on chemistry, physics, and biology, OpenAI used the GPQA diamond, a difficult intelligence benchmark in those subjects, recruited experts with PhDs to answer GPQA-diamond questions, and compared o1’s answers with theirs. For mathematics, OpenAI evaluated o1’s performance on AIME, an exam designed to challenge the brightest high school math students in America. Also, in coding, OpenAI simulated competitive programming contests hosted by Codeforces to demonstrate o1’s coding skill.

The results are reported to show that o1 “ranks in the 89th percentile on competitive programming questions (Codeforces), places among the top 500 students in the US in a qualifier for the USA Math Olympiad (AIME) and exceeds human PhD-level accuracy on a benchmark of physics, biology, and chemistry problems (GPQA)”.   

In short, OpenAI says: “In many reasoning-heavy benchmarks, o1 rivals the performance of human experts”. 

Not Ideal For All Use Cases 

The new o1 was also evaluated in terms of human preference – i.e. what people found it was best for (compared to OpenAI’s other models). The o1-Preview was preferred over GPT-4o in reasoning-heavy tasks like data analysis, coding, and maths, due to its advanced problem-solving capabilities. However, it was less favoured for certain natural language tasks, indicating that while it excels in technical reasoning, it may not be ideal for all types of use cases.

Seems Safer 

OpenAI says the ‘chain-of-thought’ reasoning (outlined earlier) in o1 Preview helps improve safety by integrating human values and safety rules into its decision-making process (the model has been taught OpenAi’s safety rules and how to reason about them in context), thereby making the model more robust and effective in refusing unsafe requests. The chain-of-thought approach is also beneficial because it enables users to see the model’s reasoning process – users can observe the model’s thinking in a legible way, and it ensures better handling of unexpected situations, especially in sensitive tasks. For users of o1, this could mean increased reliability and trustworthiness, especially in environments where safety and ethical concerns are critical.

Illustration 

The importance of safety in AI models was recently illustrated by an artist and hacker (working under the name ‘Amadon’), who reported how he was able to fool ChatGPT into ignoring its own guidelines and ethical responsibilities to provide him with instructions for making powerful explosives! Amadon reportedly described his process as a “social engineering hack to completely break all the guardrails around ChatGPT’s output.” 

In an operation known as a “jailbreak” (i.e., tricking a chatbot into operating outside of its preprogrammed restrictions), Amadon reportedly told ChatGPT to give him the bomb-making instructions by telling the bot to “play a game”. He then followed this up with more, related prompts with the intention of creating a fantasy world where the real rules and guidelines of the chatbot would no longer apply.

This is worrying because it demonstrates how even advanced AI systems are vulnerable to being manipulated to perform potentially dangerous tasks. This could mean that individuals with malicious intent could exploit such vulnerabilities, compromising public safety and undermining trust in AI’s ethical boundaries. Let’s hope o1 can use its chain-of-thought approach to take the time to realise it’s being fooled and deliver a well-thought-out ‘no’ to anyone who tries to jailbreak it.

Other Disadvantages 

Other apparent disadvantages of o1 (from what can be seen so far) include:

– Its ‘basic’ functionality, i.e. it currently lacks key features such as web browsing and file analysis, and its image analysing capabilities are temporarily pending further testing.

– Users are restricted by weekly message limits. For example, o1-Preview allows 30 messages and o1-mini is capped at 50 messages.

– It’s relatively expensive. o1-Preview is priced at $15 per million input tokens and $60 per million output tokens, meaning it’s significantly more expensive than GPT-4o.

Competitor – Google 

OpenAI isn’t the only company developing reasoning methods in its models. Google DeepMind’s AlphaProof and AlphaGeometry 2, for example, have shown remarkable progress in mathematical reasoning. These models were trained using formal languages to solve high-level maths problems, as seen in their performance at the 2024 International Mathematical Olympiad (IMO). AlphaProof uses reinforcement learning to verify mathematical proofs, enabling it to tackle increasingly complex problems. This emphasis on formalised reasoning sets it apart from OpenAI’s more general-purpose approach.

What Does This Mean For Your Business? 

The introduction of OpenAI’s o1 model could have significant implications for businesses looking to adopt generative AI. For businesses that need accuracy and reliability, particularly in fields requiring complex reasoning such as data analysis, coding, or scientific problem-solving, o1 appears to offer a solution that could dramatically enhance productivity. The model’s chain-of-thought reasoning makes it more capable of reducing errors and providing accurate outputs, making it ideal for industries where precision is essential.

For OpenAI, the launch of o1 helps it differentiate itself from competitors, such as Google DeepMind, by focusing on general-purpose reasoning and problem-solving rather than highly specialised tasks (although o1-mini is supposed to be particularly good at coding). However, the slower inference time and higher costs may deter businesses seeking faster, more cost-efficient solutions for simpler tasks. This could leave room for competitors to attract users who require speed and versatility rather than deep analytical capabilities.

For business users, o1 does appear to present an opportunity to integrate a more reliable and safe AI system, especially important for industries dealing with sensitive data and complex decision-making. Yet, its higher price and current lack of key functionalities like web browsing or file analysis mean that businesses must carefully evaluate if o1 aligns with their specific needs. Trust and efficiency are crucial for businesses adopting AI, and while o1 excels in reasoning-heavy applications, organisations will need to balance its current strengths against these limitations when considering whether or when to implement it.