Technology

• AI job losses are inevitable, but new innovations will curb the effects, Nvidia CEO Jensen Huang says
• Huang has been warned by senators before an upcoming trip to China
• US tech should 'set the global standard' Huang argues

It’s long been prophesied AI will lead to mass unemployment, with several CEOs and tech leaders warning AI will wipe out millions of jobs, and firms such as Microsoft laying off thousands of workers whilst bringing in new AI productivity tools.

Now, Jensen Huang, CEO of chip manufacturer and AI firm Nvidia, offered his (slightly stale) perspective. In an interview with CNN, Huang essentially passes job protection responsibilities over to business leaders, claiming; “If the world runs out of ideas, then productivity gains translates to job loss.”

“Everybody’s jobs will be affected. Some jobs will be lost. Many jobs will be created and what I hope is that the productivity gains that we see in all the industries will lift society,” Huang said.

Bipartisan warnings

Huang’s authority on AI is significant too, thanks to Nvidia's power in the market. The company's GPUs remain one of the most influential tech products in the world, and are largely powering AI development across the world - including in China, which is spooking some US politicians.

Huang recently received a warning written by Republican Senator Jim Banks and Democratic Senator Elizabeth Warren, Reuters reports, which advised against meeting with Chinese companies, arguing this could, “legitimize companies that cooperate closely with the Chinese military or involve discussing exploitable gaps in U.S. export controls”.

A Nvidia spokesperson saidUS technology will ‘set the global standard’ and that ‘America wins’ - with China being one of the largest software markets in the world, adding that AI software "should run best on the U.S. technology stack, encouraging nations worldwide to choose America”.

That being said, Huang has recently argued Chinese military branches will avoid using US technology because of the associated risk; “it could be, of course, limited at any time” he argued, “they simply can’t rely on it”.

He added how Chinese military services, which are already developing powerful tools, “don’t need Nvidia’s chips, certainly, or American tech stacks in order to build their military.”

This comes in response to growing concerns that Chinese companies and military agencies will use US tech to enhance capabilities.

Increasingly harsh restrictions have limited China’s access to top AI technologies, aimed at curbing China’s tech and AI advancement - but concerns remain about the threat to US national security should China use US companies to develop its capabilities.

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• Huawei has won a contract to provide digital storage for the Spanish Government
• The Chinese tech giant will store and classify court-ordered wiretaps
• This contrasts other western states that now largely avoid Huawei, and Chinese tech

Any Spanish government wiretaps carried out by law enforcement agencies will soon be managed by Chinese telecom giant Huawei thanks to a recently-won contract.

The €12.3 million contract was awarded to Huawei after a standard public procurement procedure - and the contract includes digital storage of judicially-ordered wiretaps, reports The Objective.

Huawei will supply its own high performance storage servers, OceanStor 6800 V5 for the project, which will store and classify intercepted communications and data collected through state agencies.

Mixed messages

Sectors of the National Police in Spain have grown uneasy with Huawei’s involvement in sensitive systems, with sources expressing concern over strategic inconsistencies regarding China and the state’s access to data and a potential threat to national security.

Huawei points out that no backdoor has ever been identified within its telecommunications equipment, and the company asserts that it would not answer CCP requests for intelligence, nor would its equipment be used to spy (unless you count government wiretapping contracts).

Spain’s PM Pedro Sánchez has been one of the least combative towards Huawei’s presence, with Spain remaining a close partner within the EU for the company - holding several contracts with public administrations.

Interestingly enough though, the recent procurement comes in contrast to Spain’s de facto banishment of the Chinese telecom giant from all critical infrastructure, having reduced Huawei’s presence in the 5G cores of the largest three Spanish operators to 0%, according to Euronews.

European and American governments have been increasingly distancing themselves from Chinese technology firms in recent months, primarily citing national security concerns and the threat of exfiltrated data.

An ongoing trade war between the US and China has seen firms on both sides cut off from the opposing market, with market leaders like chipmaker Nvidia saying US tariffs mean it faces a multi-billion dollar hit.

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• Iran's Information Technology Organization is seeking new cloud computing providers
• Bidders will be evaluated, graded and then tanked for suitability
• Other regions are also modernizing tech stacks

The Iranian government is apparently seeking cloud computing suppliers as it bids to rebuild its tech stack.

The nation has announced plans to evaluate, grade and rank cloud providers to determine which would be the best suit for hosting key government services, with plans to form a panel of at least three qualified cloud operators deemed fit for purpose.

The Information Technology Organization of Iran (ITOI) is now set to assess potential cloud providers based on three different standards – ISO 27017 (cloud security controls), ISO 27018 (protection of personally identifiable information), and NIST SP 900-145, which relates to US cloud computing definition.

Iran is welcoming bids for its next big cloud provider

Iran's adoption of NIST standards might be surprising given the country's ongoing tensions with the US, but its recognition of these well-regarded standards is good news for the security of citizens' data.

ITOI is now inviting providers offering IaaS, PaaS or SaaS, as well as private, public, hybrid or community cloud models.

Services like security, monitoring, support and cloud migration are also being welcomed under the new scheme, with successful candidates to be awarded a cloud service rating certificate, ultimately leading them to be listed as authorized providers that could be in for a chance of major Iranian government contracts.

However, the process might not be so simple for the Iran – many countries have made it illegal to do business with Iran, or have imposed major restrictions.

Nevertheless, Iran's efforts to modernize its tech stack reflects an ongoing trend across the world, with many other regions looking to diversify. European countries are beginning to seek local or open-source alternatives to the likes of Microsoft, while the US government continues to drive forward a scheme designed to save considerable cash on IT contracts via centralized, mass purchasing.

Via The Register

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• Security researchers from University of Toronto warn on Rowhammer flaw
• Older GPUs seem to be vulnerable
• Nvidia urges users to update as soon as possible

Nvidia is urging users to apply mitigations it provided against so-called Rowhammer attacks after new research confirmed their potential to cause serious and stealthy hardware-level compromises.

Rowhammer is an exploit of a vulnerability in dynamic RAM (DRAM), where repeatedly accessing (or "hammering") a row of memory can cause bit flips in adjacent rows. As a result, threat actors could bypass security boundaries, triggering privilege escalations, data tampering, or even denial-of-service states.

Although this is a hardware-level issue, software-based techniques can trigger and weaponize the flaw remotely.

Newer GPUs are safe

Although known for more than a decade, Rowhammer attacks have first been exploited in 2018, and even then - very rarely and in limited capacity - mostly due to their complexity and hardware dependencies.

However security researchers Chris (Shaopeng) Lin, Joyce Qu, and Gururaj Saileshwar, from the University of Toronto recently published new research demonstrating the practical use of the flaw:

"We ran GPUHammer on an NVIDIA RTX A6000 (48 GB GDDR6) across four DRAM banks and observed 8 distinct single-bit flips, and bit-flips across all tested banks," the researchers said. "The minimum activation count (TRH) to induce a flip was ~12K, consistent with prior DDR4 findings."

"Using these flips, we performed the first ML accuracy degradation attack using Rowhammer on a GPU."

The “ML accuracy degradation attack” means Rowhammer was used to degrade machine-learning model accuracy, from the usual 80% down to a depressing 1%, using a single bit flip.

Nvidia has urged users to activate the System Level Error-Correcting Code mitigation, which protects against Rowhammer on GDDR6 devices. The mitigation works by adding redundant bits and correcting single-bit errors, maintaining data reliability and accuracy.

The list of affected GPUs is rather extensive, and besides the RTX A6000, includes multiple Blackwell, Volta, and Turing products.

The full list can be found on this link - but newer GPUs come with built-in protection, Nvidia said.

Via BleepingComputer

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Today’s data and business analysts have a wealth of tools at their fingertips to do their jobs effectively. Behind every analyst team, however, is an IT leader being asked to communicate how such tools offer a Return on Investment (ROI).

Without being able to answer these questions resolutely, IT budgets will be scrutinized and, at worst, put at risk. However, the arrival of AI and IT automation may be about to flip the switch and make it much easier to prove ROI. Let’s explore…

The reporting gap

A lack of answers boils down to reporting gaps. To date, companies that have invested in advanced data analytics and data visualization platforms have fallen into the trap of neglecting the reporting that shows impact. If no one tracks the time saved from that platform or its influence on decision making, its impact goes unnoticed in the wider business.

Take a retail business as an example. Deploying predictive analytics to optimize inventory management counts for nothing without structured reporting on stock reductions, cost savings or sales improvements as outcomes.

Analysts themselves feel the drag when they aren’t given the space to communicate outcomes. A third believe reporting should be a core part of their role but is currently overlooked.

With the introduction of AI into analytics workflows, as well as increased automation, it’s high time for enterprises to turn a page. The improvements that these changes offer (both to working with data and its outcomes) make possible a more systematic approach to reporting.

New possibilities

Our recent research found that 97% of analysts are integrating AI into their workflows, with 87% using analytics automation to streamline routine tasks.

With the right platform, it's possible for analyst teams today to automate data exploration, insight generation and the way that workflow’s function. This leads to faster time-to-value, improved decision-making and, crucially, analysts can report on progress against set KPIs in a reliable manner that doesn’t rely on manual input. Automated collection of performance-based data can track things like time savings in data preparation, cost per project and even the tracing of revenue back to insights generated via analytics.

Automation also makes the output of analytics more accessible. No-code platforms allow users to visualize key findings and insights without technical knowledge. This makes it easier for any business end users to come to, and communicate, data-driven conclusions.

Finally, sophisticated analytics platforms that come with integrated generative AI functionalities allow analysts to spin up presentations, reports and workflow summaries simply through a natural language prompt. The significant relief this provides analysts in terms of time and resources saved is obvious.

A focus on results communication

While AI and automation in analytics offer immense advantages, IT leaders need to shepherd a strategy to streamline and optimize the communication of results.

First and foremost, IT leaders should define success metrics that directly measure the enterprise impact of analytics tools, such as cost savings, revenue growth or operational efficiencies. Aligning these metrics with broader organizational objectives makes reporting coming out of data initiatives much more likely to resonate in ways that other teams care about – rather than heralding technical achievements without context.

Regular and proactive communication of insights is also crucial. Data analysts should go beyond ad-hoc reporting and establish a cadence for sharing comprehensive updates with leadership teams. These reports can highlight key metrics, emerging trends and measurable outcomes, ensuring that executives remain engaged with the impact of AI and analytics automation.

By demonstrating clear ROI through ongoing reporting, organizations can secure buy-in for further investment and scale their analytics capabilities effectively. There’s also no excuse not to do it, given how frictionless automation makes the collation and reporting of such insights.

Finally, fostering a culture of data literacy is an important step toward realizing the ROI of analytics and the tools that enable it. When more business users are working with data, IT teams have greater scope to gather day-to-day feedback from their analytics investments. A wider range or team are empowered to make smarter decisions and create tangible examples of ROI that make the case for continued investment.

Workforces in which the foundations of working with data are understood are more likely to apply new AI technologies in impactful ways. It also stands to improve their own productivity. Put in these terms, the strategic, long-term case for investment in analytics and data stacks becomes easier to articulate to any internal stakeholder.

Settling a debate

Proving the ROI of data analytics tools has long been a tough challenge for IT leaders. Without tracking the impact of their investments, many organizations will have been sitting on high ROI without even knowing it. That’s changing. Advances in AI tools and automation make it easier to track and show the value of analytics with clarity. This is in addition to the democratization of analytics that can unlock all-new levels of operational efficiency.

This shift is helping IT leaders make the case to stay the course with nascent or mature analytics programs, rather than dismantling efforts that were highly viable but difficult to link to business value until now. Enterprises mastering data and analytics will readily demonstrate measurable returns, giving them the most to gain in the upcoming intelligence era of AI disruption.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

In today's data-rich environment, enterprises find themselves custodians of vast, largely untapped repositories of unstructured data. These troves, encompassing documents, emails, videos and more, represent a latent competitive advantage—a wealth of potential insights awaiting activation.

The challenge lies not in the accumulation of data, but in the effective extraction of actionable intelligence. Artificial Intelligence (AI) serves as the transformative tool, capable of converting this “dark data” into tangible business value.

Nearly 90 percent of enterprise data remains unstructured. The most significant opportunity for enterprise growth and innovation in the current landscape is thoughtful AI application. The key is moving beyond mere data collection to strategic data operationalization.

Decision-Making Challenges in the Age of Information

The sheer volume of data does not automatically translate to accelerated or improved decision-making. In fact, teams often struggle to derive relevant insights and take decisive action amid the noise. To address these challenges, enterprises should focus on three critical areas of improvement:

Breaking Down Departmental Data Silos: Siloed data impedes cross-enterprise information sharing, hindering comprehensive analysis and strategic alignment. Establishing seamless data flow between departments unlocks a holistic view of the enterprise, allowing for better and more informed decision-making.

Upgrading Legacy Systems: Legacy systems often cannot fully leverage modern data processing capabilities, limiting the potential for advanced analytics and AI integration. Modernizing infrastructure is essential to unlock the full value of enterprise data.

Transforming Regulatory Compliance: Viewing regulatory compliance as a structured framework, rather than a mere obligation, allows enterprises to proactively leverage compliance data for strategic insights and confident action. This approach transforms compliance from a cost center into a value driver.

To drive this point home, let’s consider the example of a major healthcare provider grappling with fragmented patient data dispersed across 15 disparate systems. By implementing a unified data platform, the provider can empower physicians with comprehensive patient histories during critical situations, reducing treatment delays, minimizing redundant testing and ultimately improving patient outcomes.

Enterprises don’t need more data—they need better ways to use the data they already have. When enterprises combine data quality, governance and scalable AI systems, they turn a passive asset into a strategic differentiator.

Navigating the Critical Data-AI Relationship

The symbiotic relationship between data and AI demands careful navigation. Several key considerations are paramount:

The Data Quality Imperative: The performance of AI systems is inextricably linked to the quality of the underlying data. Poor-quality data can severely limit AI's potential, leading to inaccurate outputs and flawed insights. Enterprises must prioritize data excellence as the bedrock of any successful AI initiative.

Preserving Trust in AI: AI-driven decisions are only as reliable as the data upon which they are based. Inaccuracies, biases, or "hallucinations" can erode confidence in AI outputs, hindering adoption and potentially leading to adverse outcomes. Enterprises must implement robust data validation and governance mechanisms to ensure the trustworthiness of AI systems.

Impact Multiplication: The impact of poor data quality on AI performance is not merely additive; it's multiplicative. Failing to address data quality issues can lead to compounded losses in efficiency, accuracy and competitive advantage. Enterprises must recognize the long-term consequences of neglecting data quality.

Industry Reality Check: The Real Cost of Untapped Data

Untapped data represents more than just a missed opportunity; it's a tangible competitive disadvantage. Consider the following industry-specific realities:

Financial Services: Financial institutions often struggle with outdated data systems that are ill-equipped to detect sophisticated modern fraud patterns, leaving them vulnerable to financial losses and reputational damage.

Healthcare: Fragmented patient data within healthcare systems compromises the quality of care, increases costs and hinders the development of personalized treatment plans.

Retail & CPG: Retailers collect vast amounts of consumer data but often fail to translate these insights into the personalized customer experiences now expected, resulting in lost sales and diminished brand loyalty.

The key takeaway is clear: data hoarding is not a viable strategy. Enterprises must prioritize data monetization and operationalization to unlock the full potential of their data assets.

The Data-to-Intelligence Revolution: AI as the Catalyst

A modern data engineering approach must encompass every stage of the data lifecycle, from legacy data migration and real-time ingestion to robust governance and AI-driven analytics. Key components include:

AI-Accelerated Data Migration: AI/ML-powered accelerators streamline the transition from legacy systems to cloud-native environments, minimizing disruption and accelerating time-to-value. Automated workload discovery and dependency mapping provide a structured migration plan, while AI-driven schema conversion, code refactoring and optimization reduce manual effort. Self-learning AI models analyze historical workloads and recommend performance-optimized architectures for modern platforms.

Advanced Data Engineering: Real-time data processing is essential to power AI-driven decision-making. Generative AI enhances ETL/ELT pipelines, automating data transformation and quality checks. Automated, real-time ingestion pipelines leverage AI to detect, clean and process data at scale. Predictive optimization models dynamically allocate computing resources based on workload demand, while event-driven architectures ensure instant data availability for analytics and decision-making.

Knowledge Graphs for Enterprise Data Intelligence: Generative AI-powered knowledge graphs transform fragmented enterprise data into an intelligent, structured and interconnected ecosystem. AI algorithms detect patterns and uncover insights that would otherwise be missed, while enhanced data lineage tracking ensures accuracy, transparency and trust in AI-driven decisions.

Building an AI-Ready Data Foundation: A robust data foundation is essential to support AI initiatives. This includes:

• Robust Infrastructure: Ensuring high-quality, integrated data for AI-driven insights.
• AI-Driven Governance: Automating compliance, preventing mismanagement and securing access to sensitive data.
• Smart Metadata Management: Enabling automated tagging for organization, searchability and auditability.

The data-to-AI revolution isn’t about isolated initiatives—it’s about integrating every layer of enterprise data into a responsive, scalable foundation for innovation.

Transforming Data with AI Agents: From Raw Information to Powerful Insights

We are rapidly moving beyond the era of static business intelligence dashboards and reactive data analysis. The future of enterprise decision-making lies in the hands of AI agents: intelligent, autonomous systems that proactively transform raw information into actionable insights. These aren't just souped-up analytics tools; they represent a fundamental shift in how enterprises interact with and leverage their data assets.

The key to unlocking the full potential of AI agents lies in their ability to:

Contextualize Data: AI agents don't just process data; they understand its context, relevance and implications.

Automate Insights: AI agents automate the process of extracting insights, eliminating the need for manual analysis and freeing up human resources for more strategic tasks.

Enable Proactive Decision-Making: AI agents empower enterprises to anticipate and respond to change in real-time, enabling proactive decision-making and a competitive edge.

For example: imagine a retail enterprise deploying AI agents to continuously monitor customer behavior, social media trends and competitor pricing strategies. Instead of waiting for a weekly report, these agents dynamically adjust stock recommendations, personalize marketing campaigns and optimize pricing in real-time. This level of agility was previously unattainable, but AI agents make it a reality.

This is where dark data turns into an enterprise superpower. It enables every employee—not just data scientists—to make informed decisions, guided by always-on, always-evolving intelligence.

Conclusion: From Data Possession to Data Power

In the modern enterprise, the emphasis must shift from simply possessing data to effectively leveraging it. Enterprises don't need more data; they need better ways to use the data they already have. Failing to operationalize data comes with the risk of falling behind competitors who are actively harnessing the power of AI.

The enterprises that will thrive in the decades to come are those that can successfully unlock and activate their untapped data assets using AI. The question is no longer “How much data do you have?” but “How intelligently are you using it?”

The time to act is now. The future belongs to those who can harness the hidden power of their dark data, transforming it into AI-driven business value.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Here are hints and the answers for the NYT Connections: Sports Edition puzzle for July 14, No. 294.

Here are the answers for The New York Times Mini Crossword for July 14.

Dyson, a company best known for its vacuums and hair dryers, has unveiled a new rotating farm design that aims to make food production more local, sustainable and dependable.

Here are some hints and the answers for the NYT Connections puzzle for July 14, #764.

Here are hints and answers for the NYT Strands puzzle for July 14 No. 498.

Here are hints and the answer for today's Wordle for July 14, No. 1,486.

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• MaxSun’s Mini Station fuses dual GPUs and mobile silicon into a compact desktop unit
• With 48GB of VRAM, it’s clearly built for demanding creative and AI inference tasks
• Dual Thunderbolt 5 ports and SlimSAS slots push bandwidth to a theoretical 192Gbps

MaxSun has introduced what it claims is the industry's first compact workstation built around Intel’s Core Ultra 9 285HX processor, a chip based on the Arrow Lake-HX architecture.

The MaxSun Mini Station is a compact system intended for professionals handling AI inference, model deployment, or resource-heavy creative work.

The system includes two Arc Pro B60 GPUs from MaxSun, specifically the Milestone 24G model, each equipped with 24GB of video memory - together, they provide a total of 48GB VRAM, designed to support demanding workloads like large language model interactions and long-context scenarios such as Qwen3-32B.

Dual Arc GPUs push VRAM to 48GB

There are some questions over its practical compatibility and whether such GPU arrangements can scale efficiently across different software stacks, especially those outside of AI labs.

On the CPU front, MaxSun opted for the Core Ultra 9 285HX, a 24-core processor with 8 performance cores and 16 efficient cores.

This mobile-class chip, recontextualized for desktop through the MoDT (Mobile on Desktop) strategy, forms the foundation of the Mini Station.

The processor is not removable or upgradable, which imposes a fixed ceiling on long-term flexibility.

Although the hardware choice makes sense from a manufacturing standpoint, it may raise doubts for buyers.

In terms of connectivity, the Mini Station supports one M.2 PCIe 5.0 x4, two M.2 PCIe 4.0 x4, and two SlimSAS SFF-8654 4i PCIe 4.0 x4 interfaces - combined with dual Thunderbolt 5 and dual Thunderbolt 4 ports, the system delivers a theoretical throughput of 192Gbps.

These specs suggest real potential for external GPU setups or ultra-fast local storage, important factors for those looking for the best PC for video editing or complex simulations.

The MaxSun GPUs incorporate dual fans, composite heat pipes, and a metal backplate, which should ensure thermal stability.

However, this does not eliminate concerns over performance throttling in such a compact case.

Via ITHome and Videocardz

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• Samsung has been talking about future wearables
• Earrings and necklaces could be developed
• Several companies are working on portable AI devices

Samsung has big plans for more wearables: not just in the form of the newly launched Galaxy Watch 8 and the much anticipated Galaxy Ring 2, but also in more innovative products such as smart earrings and smart necklaces.

Speaking to CNN (via Android Authority), Samsung mobile executive Won-joon Choi offered some thoughts on the next wave of wearable devices we might see – and how these devices could differ from what we have today.

"We believe [these devices] should be wearable, something that you shouldn’t carry, [that] you don’t need to carry," says Choi. "So it could be something that you wear, glasses, earrings, watches, rings and sometimes [a] necklace."

This is a long way from confirmation that a Samsung Galaxy Earring or Necklace is on the way, but it's clear that Samsung is looking into different types of technology, and weighing up what kind of device form factors could be beneficial for users.

Working and exploring

The Galaxy Watch 8 is Samsung's newest wearable (Image credit: Samsung)

Smart glasses are also mentioned there, and Samsung has been rumored to be working on a pair of smart specs for quite some time now – ready to take on the Ray-Ban Meta Smart Glasses – although nothing has been made official as yet.

Watch this space though: "We are actively working on glasses, but some people do not want to wear glasses because they change their look," says Choi in the interview. "So we are also exploring other types of devices."

No doubt some kind of AI processing will be involved in these future devices. We know that ChatGPT developer OpenAI is busy developing a hardware device that would enable you to carry an AI assistant with you, though several similar previous projects haven't worked.

Whatever these devices end up looking like, they're going to need long-lasting batteries, and we know that's something else Samsung is looking into. In the not-too-distant future, we may have a lot more wearable device types to choose from.

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Looking for a different day?

A new NYT Strands puzzle appears at midnight each day for your time zone – which means that some people are always playing 'today's game' while others are playing 'yesterday's'. If you're looking for Sunday's puzzle instead then click here: NYT Strands hints and answers for Sunday, July 13 (game #497).

Strands is the NYT's latest word game after the likes of Wordle, Spelling Bee and Connections – and it's great fun. It can be difficult, though, so read on for my Strands hints.

Want more word-based fun? Then check out my NYT Connections today and Quordle today pages for hints and answers for those games, and Marc's Wordle today page for the original viral word game.

SPOILER WARNING: Information about NYT Strands today is below, so don't read on if you don't want to know the answers.

NYT Strands today (game #498) - hint #1 - today's themeWhat is the theme of today's NYT Strands?

• Today's NYT Strands theme is… Won't you be my neighbor?

NYT Strands today (game #498) - hint #2 - clue words

Play any of these words to unlock the in-game hints system.

• TORY
• LIAR
• RIFE
• FAIL
• HEAR
• RENT

NYT Strands today (game #498) - hint #3 - spangram lettersHow many letters are in today's spangram?

• Spangram has 9 letters

NYT Strands today (game #498) - hint #4 - spangram positionWhat are two sides of the board that today's spangram touches?

First side: left, 4th row

Last side: right, 4th row

Right, the answers are below, so DO NOT SCROLL ANY FURTHER IF YOU DON'T WANT TO SEE THEM.

NYT Strands today (game #498) - the answers

(Image credit: New York Times)

The answers to today's Strands, game #498, are…

• TEACHER
• MAYOR
• JANITOR
• LIBRARIAN
• FIREFIGHTER
• SPANGRAM: COMMUNITY

• My rating: Hard
• My score: 1 hint

Although TEACHER was easy to spot – hanging out very visibly in the top left-hand corner – the rest of today's answers posed quite the word search challenge.

With the exception of MAYOR, every word was hard to work out, with JANITOR taking me quite a while – although I can use a cultural differences excuse here, as I am in the UK and we call this profession a caretaker.

That said I am very familiar with the word thanks to the opening titles of the Hanna Barbera cartoon Hong Kong Phooey and its introduction of “Henry the mild mannered janitor”.

Meanwhile, after a run of sensible, straight, and short spangrams we have returned to experimentation with today’s yellow snake ending in the middle of the puzzle. Crazy.

How did you do today? Let me know in the comments below.

Yesterday's NYT Strands answers (Sunday, July 13, game #497)

• LINEN
• WOOL
• SILK
• COTTON
• RAYON
• POLYESTER
• SPANGRAM: TEXTILES

What is NYT Strands?

Strands is the NYT's not-so-new-any-more word game, following Wordle and Connections. It's now a fully fledged member of the NYT's games stable that has been running for a year and which can be played on the NYT Games site on desktop or mobile.

I've got a full guide to how to play NYT Strands, complete with tips for solving it, so check that out if you're struggling to beat it each day.