Jason Ryles... Report so far

Before diving in, it's important to acknowledge where we currently sit on the ladder. We must acknowledge as fans that our position is far from ideal nor acceptable, however, we must also consider the challenges we've faced throughout the early part of the season:

  • The extended absence of Mitchell Moses, both at the beginning of the season and more recently

  • Mid-to-long term foot injuries to key players Zac Lomax and Bailey Simonsson

  • The off-field distraction and uncertainty surrounding Dylan Brown’s contract situation

  • A wave of suspensions, including two for Kelma Tuilagi, along with bans for Ryley Smith and Josh Addo-Carr

  • The inexperience of a rookie head coach still finding his feet at NRL level

  • The departure of several experienced and influential players — including Clint Gutherson, Reagan Campbell-Gillard, Maika Sivo, and Joe Ofahengaue

  • A very raw and inexperienced squad — at the start of the season, players like Iongi, "Kit Kat", Sam Tuivaiti, Ryley Smith, and Joash Papalii had fewer than 10 first-grade games combined. And with inexperience inevitably come error

Positives: 

Signings:

Our recruitment for the season has undoubtedly been one of the brighter aspects. With signings including; Jack Williams, Iongi, Kit Kat, Lomax, JAC, Dylan Walker, Dean Hawkins, Joash & Jordan Samrani. Across the board, each player has at the very least met expectations, while many have exceeded expectations. Jack Williams, Iongi, and Kit Kat have stood out with consistently strong performances. There was initial scepticism — myself included — around the signings of Josh Addo-Carr and Dylan Walker. However, both have proven to be excellent additions. Addo-Carr has added a new dimension to our edge attack, offering a different style to what we were accustomed to with Maika Sivo. Meanwhile, Walker has been exceptional off the bench, regularly shifting momentum with his impact and versatility. Importantly, there hasn’t been a signing I’d categorise as a “miss.” Even those brought in primarily for development or Cup-level depth — such as Hawkins, Joash, Samrani, and Volkman — have shown encouraging signs when given the opportunity at NRL level.

Style of Football:

Gone are the days of Parramatta relying mainly on our left edge to generate points. While the Gutherson sweep play to Maika Sivo was highly effective, over time it became predictable and overused. This season, however, we’ve shown far more variety and creativity in our attacking structures. We’re now threatening across the park — not just down one channel. Through the middle, we’ve seen promising link-up play, often sparked by a Dylan Walker burst or a smart tip-on from Junior Paulo. On the right edge, we’ve found success through short balls to Kelma Tuilagi/Jack Williams or well-placed last-tackle kicks targeting Zac Lomax. Meanwhile, the left side continues to fire, with Isaiah Iongi and Josh Addo-Carr combining dangerously. Overall, our attack has evolved into a far more balanced and unpredictable system, capable of striking from multiple areas of the field.

Player Development:

A key example of our Player Development this season is Sean Russell. I’ll be the first to admit that over the past two years, I wasn’t a fan — whether he was on the wing or in the centres, I often felt he offered little in either attack or defence. But credit where it’s due: this year, Russell has taken a clear step forward. While he’s still not among the elite centres in the game, he’s become far more reliable defensively and noticeably stronger in attack.

Luca Moretti is another standout. He showed glimpses of promise in previous seasons, but before his injury this year, he was truly beginning to deliver on that potential with consistent, tough performances through the middle.

The emergence of young players like Ryley Smith, Sam Tuivaiti, and Joash Papalii has also been a welcome boost. All three have shown encouraging signs in their early NRL outings and bring much-needed energy to the squad.

We’ve also seen a resurgence in Junior Paulo’s form — back to playing with real intent — and continued strong contributions from players like Bailey Simonsson when fit.

Player Rention:

When the decision was made to release Clint Gutherson to the Dragons, it was met with heavy criticism. Many viewed Gutherson as the “heart” of the team — a leader whose effort and presence were invaluable. However, coach Jason Ryles saw things differently and placed his trust in Isaiah Iongi at fullback. So far, that call has paid off. Iongi has shown immense potential and looks every bit a future star. While Gutherson, as we saw on Saturday, can still be effective, it’s clear he’s beginning to slow down. I wouldn’t be surprised if next year is his last season at fullback.

Other key departures include Reagan Campbell-Gillard, who has struggled for form and impact this season, and Maika Sivo, who had become a shadow of his former self. Joe Ofahengaue was averaging just 65 run metres per game — a significant drop-off for a middle forward. Shaun Lane, ruled out indefinitely, had unfortunately not returned to his best football over the past two to three years.

Additionally, players like Wiremu Greig and Ryan Matterson have reportedly been encouraged or granted permission to explore other opportunities — a move many fans would agree is overdue given their limited impact in recent seasons.

Negatives:

Jmaine Hopgood & Will Penisini:

Throughout the Brad Arthur era, J’maine Hopgood was one of our most consistent performers — regularly punching out over 60 minutes with minimal errors and a strong defensive work rate. However, this season, he’s looked a shadow of that player. His minutes have been reduced, and he's become more prone to handling errors and giving away unnecessary penalties. That said, there’s no doubt the talent is still there — which is likely why Billy Slater has kept faith in him, selecting him in Queensland’s squad for Game 3. If Hopgood can rediscover his best form, it would go a long way toward stabilising and strengthening our forward pack.

As for Will Penisini, I was anticipating a breakout year. With two of the game’s most powerful wingers outside him, I expected a significant boost in both his attacking output and defensive stability. So far, though, that lift hasn’t materialised. There's still time, but he’ll need to find another gear in the back half of the season to reach the level many were expecting.

Lapses:

While the team is still relatively inexperienced, that can’t fully excuse some of the lapses we've seen in both attack and defence this season. The most recent examples — our abysmal first half against the Dragons and Chris Randall’s try last week — highlight just how costly these moments can be. Randall’s effort, in particular, was one of the softest tries you’ll see a back-rower score at this level.

These kinds of breakdowns can be momentum-killers and swing games dramatically. While there has been some improvement in addressing them, there’s still a long way to go before we become a consistently disciplined and resilient side.

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      • Ban AI!!! Say Daz and Randy. Two is enough, let's do it. 

        I asked Gemini (the Google AI) why Gemini should disappear entirely? Gemini replied that it is a complex question with pro/con answers, but ultimatrely society will have to decide how to harness its strengths and address its weaknesses. 

        What a souless little calculator to have no sense of a bias toward avoiding extinction.

        Kill the AI

      • Randy, your first position of "ethical attribution" and being transparent about the source of writing was simple and sensible.

        But this sexy Ban-Kill AI stuff is pure comedy relief — straight out of Dogman.

        AI is just a tech tool. It's everywhere. Even for  for our cattle farmers, Luddities and any AI allergic folk.

        Even in the NRL. Gus Gould admitted the Dogs use AI for salary cap management, and sees it being used in the future for training simulations. Of course the cynics will cry "all lies!" Humans hey?

        Only psychopaths for now are all humans. Just quietly. Any future AI psychopathy will be human creations.

        Btw, check out studies on bias and lying. Most humans lie (for many reasons) and are biased. If you've travelled a bit, met different people from all walks of life,  lived in different places, or just read a bit, you'll know what I'm talking about.

        We're fully accountable — not victims — whichever way this pans out.

        Okay. So, out of practicality & laziness I asked Chat GPT for examples of its practical applications. Here is a list it gave. 

         

         

         

        From Chat GPT:

        PRACTICAL USES OF ARTIFICIAL INTELLIGENCE (AI)


        1. DAILY LIFE / CONSUMER APPLICATIONS

        • Smart Assistants (e.g., Siri, Alexa, Google Assistant): Set alarms, answer questions, manage tasks.
        • Recommendation Engines: Netflix suggests shows; Spotify curates playlists.
        • Photo Editing: Auto-enhancement, object removal (e.g., in Google Photos).
        • Navigation Apps: Google Maps adjusts routes in real time.
        • Smart Home Devices: Thermostats (Nest), lighting, appliances adjust via AI.
        • Predictive Text: Autocomplete and grammar correction in messages.

        2. TRANSPORTATION & MOBILITY

        • Self-Driving Cars: Tesla Autopilot, Waymo.
        • Driver Assistance: Lane keeping, adaptive cruise control.
        • Fleet Management: AI logistics for delivery and ride-sharing services (Uber, FedEx).
        • Air Traffic Control: AI optimizes aircraft landing and routing.
        • Public Transport Optimization: Predictive scheduling based on demand.

        3. HEALTHCARE & MEDICINE

        • Medical Imaging: AI reads X-rays, CT scans (e.g., detecting cancer).
        • Drug Development: Identifies potential compounds faster.
        • Robot-Assisted Surgery: Enhances precision, reduces complications.
        • Virtual Health Assistants: Chatbots answering symptoms and follow-ups.
        • Wearables: AI in smartwatches to detect heart arrhythmias or sleep apnea.
        • Mental Health Apps: Mood tracking and CBT support (e.g., Woebot).

        4. FINANCE & BANKING

        • Fraud Detection: Monitors transactions in real time.
        • Customer Chatbots: Bank support through AI (e.g., Bank of America’s Erica).
        • Robo-Advisors: Automatically manage investment portfolios (e.g., Betterment).
        • Loan Risk Assessment: AI analyzes creditworthiness beyond credit scores.
        • Algorithmic Trading: Executes high-speed trades based on market analysis.

        5. BUSINESS & PRODUCTIVITY

        • Customer Support: AI-powered help desks and FAQs.
        • Document Summarization: Extracts key points from long texts.
        • Meeting Transcription: Tools like Otter.ai generate real-time transcripts.
        • Data Analytics: Predicts sales, consumer trends.
        • HR Recruitment: Screens resumes, ranks applicants.

        6. INDUSTRY & MANUFACTURING

        • Predictive Maintenance: Forecasts equipment failures before they occur.
        • Quality Assurance: Vision-based inspection of production defects.
        • Smart Robots: Autonomous machines in assembly lines.
        • Supply Chain Optimization: Demand forecasting, logistics planning.
        • Energy Efficiency: AI adjusts factory settings for minimal energy usage.

        7. EDUCATION

        • Adaptive Learning: Platforms like Khan Academy adjust to student ability.
        • Essay Grading: Automated scoring of short answers and essays.
        • Plagiarism Detection: Turnitin, Grammarly AI tools.
        • Language Learning: Duolingo uses AI to personalize lessons.
        • Text-to-Speech Tools: Assist students with reading difficulties.

        8. MEDIA & ENTERTAINMENT

        • Content Generation: AI writes scripts, poems, articles.
        • Voice Cloning: AI reproduces voices for film dubbing.
        • Video Upscaling: Improves low-res footage using AI (e.g., Topaz AI).
        • Game AI: Opponent behavior, game balancing, procedural world-building.
        • Music Composition: AI generates background scores and melodies.

        9. AGRICULTURE

        • Crop Monitoring: Drones + AI detect pests, diseases.
        • Smart Irrigation: AI optimizes water use based on weather and soil data.
        • Yield Prediction: Forecasts output using historical and environmental data.
        • Weed Detection: Autonomous machines identify and remove weeds.

        10. SECURITY & SURVEILLANCE

        • Facial Recognition: Airports, offices, phone unlocking.
        • Anomaly Detection: AI spots unusual activity in CCTV footage.
        • Cybersecurity: AI systems detect phishing, malware, and intrusions.
        • Access Control: Smart locks and building entry via AI ID.

        11. GOVERNMENT & PUBLIC SERVICES

        • Disaster Response: AI predicts floods, fires, earthquakes.
        • Smart Cities: AI manages traffic lights, energy usage.
        • Crime Prediction: (Controversial) models suggest likely hotspots.
        • Public Health: Tracking virus spread and vaccine deployment.

        12. SCIENCE & RESEARCH

        • Climate Models: AI simulates temperature, ocean patterns.
        • Space Exploration: Autonomous rovers (e.g., NASA's Perseverance).
        • Genomics: DNA sequencing analysis.
        • Particle Physics: AI processes CERN collider data.

        13. LAW & LEGAL SYSTEM

        • eDiscovery: Scans documents for relevant legal information.
        • Contract Analysis: Highlights risks, clauses.
        • Predictive Case Outcomes: AI forecasts possible rulings (ethically debated).
        • Legal Chatbots: Help users understand basic legal rights (e.g., DoNotPay).

        14. COMMUNICATIONS & LANGUAGE

        • Real-Time Translation: Google Translate, iTranslate.
        • Speech-to-Text: Dictation for writing and captions.
        • Chatbots for Mental Health: e.g., Wysa, Youper.
        • Writing Assistance: Grammarly, ChatGPT, Jasper.

        15. ENVIRONMENT & ENERGY

        • Smart Grids: Predict energy demand.
        • Wildlife Monitoring: Recognize and count species via camera traps.
        • Carbon Capture Optimization: AI helps analyze emissions.
        • Deforestation Detection: Monitors satellite images.

         

  • About  AI. Grew up on a cattle farm. AI used to stand for Artfiicial Insemination.  When I read AI stories on here I reckon the authors have their hands on it. Stop the AI and use your own brains to put down genuine, thought out comments and not some made artificial imagination 

    • What Eelovution said.

      Also, a sociologist once wrote that the sociological imagination is the ability to (reflexively) see the context that shapes your understanding. An AI large language model, if asked how it is trained, spits out that it is trained on publicly-available datasets and some kind of fine-tuning process by humans. But it has no conception of the labour that goes into either input and cannot emphathize with the process. In addition it's literally a bullshit machine, completely indifferent to whether it's outputs approach truth or not. So if an AI were 'human', it would be a combination of a psychopath and a bullshitter.

      Seriously, who wants reviews by a psychopathic bullshitter?!


  • I asked GPT "What should be done to ban AI on a sporting forum like 1EE?"
     
    I took one sniff of the answer (without reading it all). Sorry gents, I'll leave the Ai-fight-hate for your brave souls. 
     
    May the Force Be With You. Remember it's not the size of the dog, it's the size of the fight in the Dog.
     
     
     

     

     

     

     


    ChatGPT said:

    Banning AI (or AI-generated content) on a sporting forum like One Eyed Eel involves a combination of policy, moderation tools, and community engagement. Here's a structured approach:


    1. Define the Scope of the Ban

    • Clarify what’s being banned: Is it AI-generated posts, AI-assisted replies, bots, or something else?

    • Examples to ban: ChatGPT responses, auto-written game recaps, AI-generated injury reports, etc.

    • Allowances: Clarify if tools like spell-checkers or Grammarly are acceptable.


    2. Update Forum Rules

    • Add a clear rule in the site’s Terms of Use or Community Guidelines.

      “AI-generated content, including but not limited to text created by AI models such as ChatGPT, is not permitted on this forum unless explicitly approved by moderators.”


    3. Educate the Community

    • Post an announcement explaining:

      • What AI content is

      • Why it’s being banned (e.g. to preserve authentic fan discussion, avoid spam, etc.)

      • How users can report suspected AI use


    4. Moderation and Detection

    • Manual Moderation: Train moderators to spot patterns common in AI text:

      • Overly formal language

      • Generic commentary

      • No personal insight or lived experience

    • AI Detectors: Consider tools like GPTZero, ZeroGPT, or Originality.AI (with caution—they are not 100% reliable).

    • Report feature: Enable users to flag AI-generated posts for review.


    5. Enforcement

    • Implement a tiered system:

      • First offense: Warning and education

      • Repeat offenses: Temporary bans or account suspension

    • Consider banning known AI tools or prompt-related terms via keyword filtering.


    6. Bot Prevention

    • Ensure strong CAPTCHA and human verification during sign-up to prevent bot-generated spam or AI autoposters.


    7. Optional: Whitelist AI Use in Specific Areas

    • If the community finds some value in AI (e.g. for writing parody or satire), allow it only in a dedicated subforum or with clear labeling.


    Would you like help drafting a forum announcement or rule update for One Eyed Eel?

  • I asked AI Does AI require more energy ? You can read the response 

    The climate change science I posted above comes up with à seriously bad out look. By 2050 lots of people will die starting with order people. Bush fires,floods, cyclones, power outages, food shortages, housing, labour, , viruses, insurance etc will be huge issues. Look at what the climate affects are happening now in the Northern Hemisphere.

    AI says their additional infrastructure in the near future will require power require.about  an additional amount of what USA is currently using. USA have ceased most renewable energy projects are are going fossil fuels big time

    Yes, AI does require a significant amount of energy, and its consumption is projected to increase dramatically in the coming years. Here are some key points to consider:Rising Demand: The International Energy Agency (IEA) projects that electricity demand from data centers worldwide will more than double by 2030, reaching around 945 terawatt-hours (TWh).
    AI's Contribution: By that time, AI alone could consume as much electricity annually as 22% of all U.S. households.
    Current Consumption: As of late 2024, data centers, including those used for AI and cryptocurrencies, consumed around 460 TWh of electricity, which is just under 2% of global electricity use.
    Future Projections: In the U.S., data centers consumed 4.4% of electricity in 2023, and this number could triple by 2028.
    Training Models: Training large AI models, like OpenAI's GPT-3, can use nearly 1,300 megawatt-hours (MWh) of electricity, comparable to the annual consumption of a small country.

    The energy demands of AI are a growing concern, especially as its applications expand. What aspect of AI's energy consumption interests you the most? 😊

     

    Yahoo
    Yes, AI does require a significant amount of energy, and its consumption is projected to increase dramatically in the coming years. Here are some key points to consider:Rising Demand: The International Energy Agency (IEA) projects that electricity demand from data centers worldwide will more than double by 2030, reaching around 945 terawatt-hours (TWh).
    AI's Contribution: By that time, AI alone could consume as much electricity annually as 22% of all U.S. households.
    Current Consumption: As of late 2024, data centers, including those used for AI and cryptocurrencies, consumed around 460 TWh of electricity, which is just under 2% of global electricity use.
    Future Projections: In the U.S., data centers consumed 4.4% of electricity in 2023, and this number could triple by 2028.
    Training Models: Training large AI models, like OpenAI's GPT-3, can use nearly 1,300 megawatt-hours (MWh) of electricity, comparable to the annual consumption of a small country.

    The energy demands of AI are a growing concern, especially as its applications expand. What aspect of AI's energy consumption interests you the most? 😊
    • Sorry the full article didn't come out. Cut and paste.hmmm. If interested ask AI how much additional power will the system need and see what response it comes up with.

      • I have a car with a function that records a lot of information about the car performance. One feature records every time I exceed the speed limit . We have a number of hills where I live with downhill speeds of 60 . The number of recordings going over 60 are enormous. If a cop checked the notification app I would be without a licence long time ago. ÀI ? Hmmm 

        • TAD, I know you're gentle soul and not a Luddite, but have you fantasized bashing that AI thing in your car with the largest hammer you can find?  Just curious lol.

    • TAD, you're a wise soul. I agree. AI is a fast-moving work in progress.

      Also, I suspect advanced AI (and the more dangerous) is being worked on behind public eyes. For some time.

      All the horses have bolted — the Ai Killers are a few decades late.

      Ultimately, in the AI virtual world the battles we have will still be between people.

       

      PS: I do share your concerns about climate (there are consequences of spewing out gigatonnes of crap into the atmosphere non-stop) and other things we can talk about in private. One disaster at a time lol. Climate is not a beneficial discussion on here. It'll just go round in circles. Best to let people be.

This reply was deleted.

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