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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 Thursday's puzzle instead then click here: NYT Strands hints and answers for Thursday, July 31 (game #515).

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.

• Today's NYT Strands theme is… Slithering away

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

• CANADA
• TRADER
• PLACE
• BEAT
• POLAR
• CLEAR

• Spangram has 7 letters

First side: left, 5th row

Last side: right, 6th row

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

The answers to today's Strands, game #516, are…

• ADDER
• PYTHON
• COBRA
• MAMBA
• VIPER
• ANACONDA
• RATTLER
• SPANGRAM: SERPENT

• My rating: Hard
• My score: 1 hint

I was expecting the spangram to spell out “snake”, but that would be too obvious – and too short.

Despite knowing what we were searching for, I struggled to find a SERPENT – but did locate plenty of non-game words, so I took a hint to get me going. ADDER set me off and from there I slithered to glory.

That said, I did tap out “rattle” instead of RATTLER about three times before adding the R once there was no other option.

• SPONGE
• LAVA
• BUNDT
• FRUIT
• POUND
• CHEESE
• FUNNEL
• SPANGRAM: PIECE OF CAKE

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.

A new Quordle 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 Thursday's puzzle instead then click here: Quordle hints and answers for Thursday, July 31 (game #1284).

Quordle was one of the original Wordle alternatives and is still going strong now more than 1,100 games later. It offers a genuine challenge, though, so read on if you need some Quordle hints today – or scroll down further for the answers.

Enjoy playing word games? You can also check out my NYT Connections today and NYT Strands today pages for hints and answers for those puzzles, while Marc's Wordle today column covers the original viral word game.

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

• The number of different vowels in Quordle today is 4*.

* Note that by vowel we mean the five standard vowels (A, E, I, O, U), not Y (which is sometimes counted as a vowel too).

• The number of Quordle answers containing a repeated letter today is 0.

• No. None of Q, Z, X or J appear among today's Quordle answers.

• The number of today's Quordle answers starting with the same letter is 2.

If you just want to know the answers at this stage, simply scroll down. If you're not ready yet then here's one more clue to make things a lot easier:

• A

• M

• W

• A

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

The answers to today's Quordle, game #1285, are…

• ACTOR
• MEALY
• WIDTH
• ADOBE

Knowing letters that go together can really speed up a Quordle game. Today, it was predicting the TH in WIDTH and LY in MEALY that helped me complete the puzzle.

That said, I still struggled with a wrong guess, trying “maple” ahead of the correct word.

As with many Quordle games ADOBE was pulled from my memory bank of previous games – this is its third entry since March.

The answers to today's Quordle Daily Sequence, game #1285, are…

• WREST
• LATHE
• ALERT
• WOULD

• Quordle #1284, Thursday, 31 July: STYLE, VALET, AGONY, ALLOY
• Quordle #1283, Wednesday, 30 July: DEBAR, ADMIN, FOLIO, USAGE
• Quordle #1282, Tuesday, 29 July: BATCH, TOPIC, MURKY, BUNCH
• Quordle #1281, Monday, 28 July: CANDY, TRYST, SHIRT, FORGO
• Quordle #1280, Sunday, 27 July: TRAWL, BALER, PIANO, MINCE
• Quordle #1279, Saturday, 26 July: MUDDY, SAINT, KINKY, POLAR
• Quordle #1278, Friday, 25 July: BONUS, RESIN, CEDAR, MADAM
• Quordle #1277, Thursday, 24 July: AGONY, VERVE, GLEAN, MINUS
• Quordle #1276, Wednesday, 23 July: OZONE, PENCE, ROOMY, WIDER
• Quordle #1275, Tuesday, 22 July: OPTIC, GIDDY, VOCAL, ADULT
• Quordle #1274, Monday, 21 July: KNEED, SNAIL, PINTO, FEAST
• Quordle #1273, Sunday, 20 July: GRACE, COUNT, EGRET, GIANT
• Quordle #1272, Saturday, 19 July: EARLY, CLICK, TRITE, SPREE
• Quordle #1271, Friday, 18 July: CINCH, FOYER, FUDGE, TAFFY
• Quordle #1270, Thursday, 17 July: CRESS, TABOO, POWER, HATER
• Quordle #1269, Wednesday, 16 July: UNCLE, NADIR, REMIT, BROOM
• Quordle #1268, Tuesday, 15 July: VILLA, FLECK, TIGER, CRANE
• Quordle #1267, Monday, 14 July: SURGE, PIZZA, PAPER, POPPY
• Quordle #1266, Sunday, 13 July: KAYAK, DECRY, RUDDY, HATER

Cybersecurity and resilience are essential for organizations striving to succeed in our highly connected world. With threats evolving at a breakneck pace, protecting your business requires more than vigilance. It demands a two-pronged strategy. First, proactive measures that detect and stop attacks before they happen. Second, an agile, efficient response plan to recover quickly if a breach occurs.

One of the most misunderstood aspects of cybersecurity attacks is timing. Cyberattacks don’t begin when they are detected; they begin when access is gained. This could be weeks or even months before detection. Studies suggest that the period between the disclosure and exploitation, known as “dwell time,” has a global median of around ten days.

During this window, attackers operate in stealth mode. They analyze your systems, identify gaps and vulnerabilities, and position themselves strategically for maximum impact. Attackers exploit this period to steal sensitive data, disrupt operations, or deploy malware like ransomware.

AI is now reshaping the timing and nature of these attacks. A report from the UK’s National Cyber Security Centre (NCSC) highlights a growing disparity between organizations equipped to counter AI-enabled threats and those that falter. Worse, AI has the potential to increase the attack surface while simultaneously reducing dwell time. This dual dynamic will challenge even the most prepared defenders.

Every technological leap creates the potential for new security gaps, and AI is no exception. The NCSC stresses that improperly integrated AI systems can expose vulnerabilities. Generative AI (GenAI), for instance, introduces risks related to data exposure, manipulation of outputs, sensitive information leaks and even injection attacks that compromise AI tools.

Maintaining the integrity of training and inference data is becoming a growing challenge, especially as the data itself becomes more distributed. Nearly 90% of companies surveyed in Dell’s Global Data Protection Index recognize AI will generate large volumes of data requiring robust protection.

Yet 65% of organizations back up 50% or less of their total AI data, according to Enterprise Strategy Group research. This gap underscores an urgent need for comprehensive data protection strategies across infrastructure, operations and governance.

The modern world of cyber threats requires smarter, faster responses. Proactive defense rooted in zero-trust principles is critical. Zero-trust is an architectural approach to security versus a product you buy.

It never trusts and always verifies legitimate business use before granting anyone or anything access to resources. This means that users and devices are not trusted by default, even if they’re connected to a permissioned network and even if they were previously verified.

The ability to advance cybersecurity maturity starts by focusing on three core practice areas: Reducing the attack surface, detecting and responding to threats, and recovering from potential breaches.

Reducing the attack surface literally means making it harder for the bad actors to get into your network, move around and cause havoc. This requires a multilayered approach, starting with penetration testing and vulnerability assessments to identify and address potential security gaps that require immediate attention.

Other critical measures include network segmentation, strict access controls, isolating sensitive data and consistently updating software and systems to mitigate exposure to risks.

Yet, no matter how much the attack surface is reduced, breaches can still occur. Therefore, companies must also work on the second pillar - actively identifying and addressing potential security incidents and malicious activities in the earliest stages of a breach.

Managed Detection and Response (MDR) solutions harness the power of AI to monitor systems in real time, detect unusual activity and neutralize threats before they escalate. Whether it’s anomalies like strange login patterns, unusual traffic or tampered data, these systems catch issues early.

When combined with automation, these systems can immediately isolate compromised accounts or devices, preventing malicious actors from moving deeper into the network.

But detection goes beyond surface anomalies. Advanced analytics analyze data to granular levels, identifying even subtle warning signs of potential attacks. These tools can detect when data has been tampered with, signaling a possible breach before damage spreads. This foresight is invaluable, enabling organizations to act well before a threat spirals into a full-blown crisis.

No defense strategy is foolproof, even with strict security protocols and advanced detection systems in place. Human error, insider threats or highly sophisticated cyberattacks can and will occasionally bypass safeguards. When this happens, recovery becomes the priority. Recovery can be guided by three AI-powered principles: isolation, immutability and intelligence.

An isolated recovery environment protects critical backups by separating them from normal operations. This containment prevents attackers from tampering with the stored data. Additionally, ensuring immutability means that backups cannot be altered, deleted or overwritten, providing a secure foundation for restoration. Automated System Recovery (ASR), for example, is a hardware-based tool that can bring compromised servers back to their last functioning state quickly.

AI-powered intelligence completes the recovery process. Analytical tools can review data for signs of corruption, look for anomalies like unauthorized encryption or mass deletions, and assess damage levels across the entire digital infrastructure. These forensic insights help businesses better understand the severity and scope of an attack while preparing for future resilience.

We’re at a pivotal juncture for cybersecurity. Attackers are using AI to outmaneuver defenses more rapidly than ever before, but defenders are equally equipped to use the same technology to strengthen their protection and response strategies. By focusing on reducing vulnerabilities, detecting threats early and empowering teams with recovery mechanisms, organizations can achieve a resilience that’s critical for both surviving and thriving in today’s threat environment.

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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

The enterprise software playbook seemed clear: everything moves to the cloud eventually. Applications, databases, storage: they all followed the same inevitable arc from on-premises to software-as-a-service.

But with the arrival and boom of artificial intelligence, we’re seeing a different story play out, one where the cloud is just one chapter rather than the entire book.

AI workloads are fundamentally different beasts than the enterprise applications that defined the cloud migration wave. Traditional software scales predictably, processes data in batches, and can tolerate some latency.

AI systems are non-deterministic, require massive parallel processing, and often need to respond in real-time. These differences reshape the entire economic equation of where and how you run your infrastructure.

Take the challenge of long-running training jobs. Machine learning models don't train on schedule; they train until they converge. This could be hours, days, or weeks. Cloud providers excel at providing infrastructure at short notice, but GPU capacity at hyperscalers can be hard to get without a 1 year reservation.

The result is either paying for guaranteed capacity you might not fully use, or risking that your training job gets interrupted when using spot instances to reduce costs.

Then there's the inference challenge. Unlike web applications that might see traffic spikes during Black Friday, AI services often need to scale continuously as customer usage grows.

The token-based pricing models that govern large language models make this scaling unpredictable in ways that traditional per-request pricing never was. A single customer query might consume 10 tokens or 10,000, depending on the complexity of the response and the size of the context window.

The most intriguing development involves companies discovering hybrid approaches that acknowledge these unique requirements rather than abandoning the cloud. They're using on-premises infrastructure for baseline, predictable workloads while leveraging cloud resources for genuine bursts of demand.

They're co-locating servers closer to users for latency-sensitive applications like conversational AI. They're finding that owning their core infrastructure gives them the stability to experiment more freely with cloud services for specific use cases.

This evolution is being accelerated by regulatory requirements that simply don't fit the cloud-first model. Financial services, healthcare, and government customers often cannot allow data to leave their premises.

For these sectors, on-premises or on-device inference represents a compliance requirement rather than a preference. Rather than being a limitation, this constraint is driving innovation in edge computing and specialized hardware that makes local AI deployment increasingly viable.

The cloud providers aren't standing still, of course. They're developing AI-specific services, improving GPU access, and creating new pricing models. But the fundamental mismatch between AI's resource requirements and traditional cloud economics suggests that the future won't be a simple rerun of the SaaS revolution.

Instead, we're heading toward a more nuanced landscape where different types of AI workloads find their natural homes. Experimentation and rapid prototyping will likely remain cloud-native. Production inference for established products might move closer to owned infrastructure. Training runs might split between cloud spot instances for cost efficiency and dedicated hardware for mission-critical model development.

The approach represents a step toward infrastructure strategies that match the actual needs of AI systems rather than forcing them into patterns designed for different types of computing

The most successful AI companies of the next decade will likely be those that think beyond the cloud-first assumptions and build infrastructure strategies as sophisticated as their algorithms.

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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