u/Ok-Sheepherder1675

Now i know this opinion will get me called as gambhir's pr and whatnot but honestly i feel India should never qualify for wtc final. What did we do the last time we qualified for WTC final, and there was no gambhir to blame? We played ipl until a week before the final ,went to the final totally unprepared with an exhausted squad playing t20 until a week before, and got our assess handed to us. And even in 2027 assuming by a miracle we win 9/9 remaining tests and qualify for WTC final we will repeat same process and gift the opponent a trophy.
So i believe until BCCI decides and our players who are in WTC final squad are ready to sacrifice their 1 season of ipl go to england and practice for 45 days earlier in the conditions of the WTC final we shouldn't even wish to qualify.

Just watched another one of his mom half centuries today, and he is performing in each and every match of dpl, although the quality is much lower than ipl, it is pretty good to see a kkr opener perform this good. Love to know the community's opinion on this take?

I mean the last few weeks, every entire cricket subreddit has problems with ipl flat pitches. These 250+ pitches have been there since 2024 ipl. since then we have won each and every t20 series home and away prior to ireland. Nobody was downplaying abhishek or ishan or anyone scoring on these pitches until we lost. Instead, we were busy glazing them as next yuvraj , kohli and whatnot. Only because we lost , the english media and us fans have made the pitches of ipl as one of the main reasons for players' downfall. Even GG was praised as a brilliant t20 coach until surya's tenure got over.

Imagine for a moment that hank was onto fring right before the events of season 1, and he roped in Walter to infiltrate gus's ecosystem as a cook. Got everything exactly he wanted and arrested gus. How would he have fared in jail? Would he be able to manipulate jailmates or would he die in jail violence? Or something else?

I mean looking at our current squad we obviously have a great potential and all of them have started to fire but perhaps it is too late for us this season. So, we will have for 2027 an in-form Allen, Raghuvanshi, green, Rinku, Narine, Tyagi along with Harshit rana, Powell, Manish Pandey, Anukul Roy. This could actually be a serious title winning squad if they find a good opener- captain. But just like last 2 cycles we would be peaking in last year of mega auction cycle only to lose everything over in mega auction

I’m a second-year Computer Engineering student from India looking for a laptop mainly for:

* Machine Learning * Deep Learning * PyTorch / TensorFlow * Computer Vision * Some transformer/LLM experimentation * CUDA programming * Local inference * Research/projects/hackathons

I’m NOT looking mainly for gaming, although occasional gaming is fine.

Budget:

* ₹1,20,000 INR * Around $1400 USD

Current understanding after researching Reddit:

* NVIDIA is basically mandatory because of CUDA * RTX 4060 seems like the best value/performance option * 8GB VRAM is probably enough for learning + medium workloads * Cooling/TGP matters more than thin design * 32GB RAM upgradeability is important

Priorities:

1. Strong cooling / sustained performance
2. Reliable thermals
3. Upgradeable RAM + SSD
4. Good Linux compatibility (optional but preferred)
5. Long-term durability
6. Decent battery life for college use

Currently considering:

* Lenovo LOQ * Lenovo Legion * ASUS ROG Strix * ASUS TUF * Acer Predator Helios Neo 16

Main confusion:

* Is RTX 4060 enough for serious ML/DL student workflows in 2026? * Which brands/models have the best thermals and least issues long term?

Would appreciate advice from people actually doing ML/DL or local AI workloads on laptops.

[India] ₹1,20,000 budget laptop for heavy ML/DL + local LLM work as a Computer Engineering student

LAPTOP QUESTIONNAIRE

Total budget (in local currency) and country of purchase. Please do not use USD unless purchasing in the US:

₹1,20,000 INR (around $1400 USD) — India

Are you open to refurbs/used?

Prefer new, but open to refurbished if reliability and warranty are good.

How would you prioritize form factor (ultrabook, 2-in-1, etc.), build quality, performance, and battery life?

Performance and cooling are the highest priority.
Good build quality and upgradeability are important.
Battery life matters for college use but not at the expense of performance.
Not interested in 2-in-1 or touchscreen laptops.

How important is weight and thinness to you?

Moderately important. I can handle a heavier laptop if thermals and sustained performance are much better.

Do you have a preferred screen size? If indifferent, put N/A.

15–16 inches preferred.

Are you doing any CAD/video editing/photo editing/gaming? List which programs/games you desire to run.

Main use case is:

• Machine Learning / Deep Learning
• PyTorch
• TensorFlow
• CUDA programming
• Computer Vision
• Local LLM inference
• Some fine-tuning
• VS Code
• Docker
• Linux dual boot possibly

Also occasional gaming and general productivity.

If you're gaming, do you have certain games you want to play? At what settings and FPS do you want?

Not a major priority, but I may play:

• Cyberpunk 2077
• GTA V/VI
• Valorant
• Elden Ring

High settings at stable FPS would be nice.

Any specific requirements such as good keyboard, reliable build quality, touch-screen, finger-print reader, optical drive or good input devices (keyboard/touchpad)?

Important:

• NVIDIA GPU (likely RTX 4060 or better)
• Good thermals/cooling
• High GPU wattage (TGP)
• Upgradeable RAM and SSD
• Reliable long-term build quality
• Good keyboard
• Decent Linux compatibility preferred

Not important:

• Touchscreen
• Fingerprint reader
• OLED display

Leave any finishing thoughts here that you may feel are necessary and beneficial to the discussion.

From my research, RTX 4060 laptops seem to offer the best value for ML/DL students, but I’m unsure whether spending extra for a 4070 is worth it.

Currently considering:

• Lenovo LOQ
• Lenovo Legion
• ASUS ROG Strix
• ASUS TUF
• Acer Predator Helios Neo 16

Would appreciate recommendations from people actually doing ML/DL or local AI workloads on laptops, especially regarding thermals, reliability, and real-world CUDA performance.

[India] ₹1,20,000 budget laptop for heavy ML/DL + local LLM work as a Computer Engineering student

LAPTOP QUESTIONNAIRE

Total budget (in local currency) and country of purchase. Please do not use USD unless purchasing in the US:

₹1,20,000 INR (around $1400 USD) — India

Are you open to refurbs/used?

Prefer new, but open to refurbished if reliability and warranty are good.

How would you prioritize form factor (ultrabook, 2-in-1, etc.), build quality, performance, and battery life?

Performance and cooling are the highest priority.
Good build quality and upgradeability are important.
Battery life matters for college use but not at the expense of performance.
Not interested in 2-in-1 or touchscreen laptops.

How important is weight and thinness to you?

Moderately important. I can handle a heavier laptop if thermals and sustained performance are much better.

Do you have a preferred screen size? If indifferent, put N/A.

15–16 inches preferred.

Are you doing any CAD/video editing/photo editing/gaming? List which programs/games you desire to run.

Main use case is:

• Machine Learning / Deep Learning
• PyTorch
• TensorFlow
• CUDA programming
• Computer Vision
• Local LLM inference
• Some fine-tuning
• VS Code
• Docker
• Linux dual boot possibly

Also occasional gaming and general productivity.

If you're gaming, do you have certain games you want to play? At what settings and FPS do you want?

Not a major priority, but I may play:

• Cyberpunk 2077
• GTA V/VI
• Valorant
• Elden Ring

High settings at stable FPS would be nice.

Any specific requirements such as good keyboard, reliable build quality, touch-screen, finger-print reader, optical drive or good input devices (keyboard/touchpad)?

Important:

• NVIDIA GPU (likely RTX 4060 or better)
• Good thermals/cooling
• High GPU wattage (TGP)
• Upgradeable RAM and SSD
• Reliable long-term build quality
• Good keyboard
• Decent Linux compatibility preferred

Not important:

• Touchscreen
• Fingerprint reader
• OLED display

Leave any finishing thoughts here that you may feel are necessary and beneficial to the discussion.

From my research, RTX 4060 laptops seem to offer the best value for ML/DL students, but I’m unsure whether spending extra for a 4070 is worth it.

Currently considering:

• Lenovo LOQ
• Lenovo Legion
• ASUS ROG Strix
• ASUS TUF
• Acer Predator Helios Neo 16

Would appreciate recommendations from people actually doing ML/DL or local AI workloads on laptops, especially regarding thermals, reliability, and real-world CUDA performance.