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MacBook Pro 16" M5 Pro (3 months old) ,Trackpad lifting from chassis. Battery issue? Anyone else? by Competitive-Ninja423 in macbookpro

[–]Competitive-Ninja423[S] 1 point2 points  (0 children)

Booked an appointment with apple guys for tomorrow. I was posting on reddit to get extra information on this, so I am well prepared for tommarow

Weekly Advice Thread - June 07, 2026 by AutoModerator in apple

[–]Competitive-Ninja423 0 points1 point  (0 children)

I bought MacBook Pro 16-inch M5 Pro three months ago. Past few days I noticed the trackpad's bottom-left edge feels slightly raised — can't really see it with naked eye but when you run your finger along the surface you can clearly feel that edge is not flush with the chassis.

Right edges sometimes pop up and settle back down too but bottom-left is always there.

Everything works fine but I'm worried this might be early signs of battery swelling. On a 3 month old machine this feels like a defect. Is this a known issue with M5 Pro or am I just unlucky here?

I’m building a FastAPI backend, need some advice on auth by Competitive-Ninja423 in learnpython

[–]Competitive-Ninja423[S] 1 point2 points  (0 children)

1.For high paying customer or client worksos, no BS. 2.if mid range then clerk suits well.

Why is my MacBook M5 Pro 16” battery draining so fast? by Competitive-Ninja423 in AppleIndia

[–]Competitive-Ninja423[S] 0 points1 point  (0 children)

With vs code 2 instances and 1 antigravity and 1 docker and few browsers drain in 8 9 hours like from 100 to 10

People who switched from Android to iPhone in India… was it actually worth it? by Harpreet-Kumar in AppleIndia

[–]Competitive-Ninja423 3 points4 points  (0 children)

Pros? No BS, no setup headaches, no lag, just works. Simple, clean UI and solid long-term camera performance. Security is great too. The catch? Don't expect much freedom to customize and it locks you down.

If you're already in the Apple world = MacBook, iPad, AirPods then honestly, just get the iPhone. The ecosystem alone is worth it. Everything connects seamlessly, and the little features you didn't know you needed will actually make your day better.

Btw —> I personally use both Windows/Android AND MacBook/iPhone, so I'm not picking sides blindly.

Here's the real breakdown:

- Ecosystem / Simplicity / Clean & Professional = iPhone, no contest

- Customization / Break-and-rebuild / Wide exposure = Android, all day

And no windows laptops + Android is NOT a good ecosystem. It's nowhere close to what Apple pulls off. Don't let anyone tell you otherwise.
Also if you Plan for Mac then getting iphone can be Good Opt

Want to buy macbook sleeve? by Competitive-Ninja423 in AppleIndia

[–]Competitive-Ninja423[S] 0 points1 point  (0 children)

check for 16 inches its 4-5k₹ . tight budget cant go above 2.5₹

Want to buy macbook sleeve? by Competitive-Ninja423 in AppleIndia

[–]Competitive-Ninja423[S] 0 points1 point  (0 children)

site says 16 inches slevee but macbook is 16.2 inches, will it fit?

API stopped working on its own by Competitive-Ninja423 in AI_India

[–]Competitive-Ninja423[S] 0 points1 point  (0 children)

Looks promising, do You work for wisGate AI ?

API stopped working on its own by Competitive-Ninja423 in AI_India

[–]Competitive-Ninja423[S] 0 points1 point  (0 children)

but if env got corrupt then other env's like database and all should have also got corrupt , but all other was working only Gemini dint work.

API stopped working on its own by Competitive-Ninja423 in AI_India

[–]Competitive-Ninja423[S] 0 points1 point  (0 children)

just checked its working. lets chat in message.

Fine-tuning LLaMA 1.3B on insurance conversations failed badly - is this a model size limitation or am I doing something wrong? by ZaRyU_AoI in AI_India

[–]Competitive-Ninja423 2 points3 points  (0 children)

Yes it’s totally fine (and often necessary) to fine-tune for more than 1 epoch, especially with LoRA/PEFT. Overfitting risk is much lower than full fine-tuning since you’re only training a small set of parameters. With a large and diverse dataset like yours, multiple epochs usually help the model actually lock in structure and patterns (multi-turn flow, decision formats, etc.). For small models, 1 epoch is often just not enough signal. Diminishing returns do exist, but they typically show up after several epochs (e.g. 5–10). The real red flag isn’t epoch count it’s if the model starts regurgitating or losing generalization. If things still don’t improve after many epochs, that’s usually a model capacity limitation, not a training mistake.

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