I was getting a severe issue with @Discover team as they don’t give me a proper solution and just pass the call here and there and finally say sorry we can’t do anything.
I was getting rejected regarding an issue with my previous account where it is closed already and 3 yrs
@amazon Thank you @amazon . Would be much helpful and need of the hour as I was seriously fed up with the other supply chains.
Better maintain the reasonable prices though.
AI / ML Engineer in 2026, please learn:
One ML stack deeply:- PyTorch or JAX, not just .fit(), but GPU memory, kernels, mixed precision, profiling, and why your model OOMs at 3am.
Data:- Where it comes from, how it lies, how it drifts, how labels break, how leakage sneaks in, and why 80% of model failures are upstream.
Statistics:- Bias vs variance, confidence intervals, calibration, distribution shift, and why “95% accuracy” is often meaningless.
Loss functions:- What you are actually optimizing, how it shapes behavior, and how bad losses silently create bad products.
Evaluation:- Real-world metrics, not Kaggle ones. Offline vs online. Regression tests for models. When numbers lie.
Training:- Distributed GPUs, gradient accumulation, checkpointing, reproducibility, and how to not lose a 3-day run to one crash.
LLMs: Tokenization, attention, context limits, KV cache, LoRA vs fine-tuning vs RAG, and where hallucinations are born.
Inference:- Batching, quantization, vLLM, streaming, cold starts, GPU vs. CPU, and why serving is harder than training.
Retrieval:- Embeddings, chunking, hybrid search, reranking, grounding, and why most RAG systems fail quietly.
Pipelines:- Feature stores, offline vs. online data, backfills, late events, schema evolution, and broken joins.
Monitoring:- Drift, outliers, token spend, latency, hallucination rate, and silent quality decay.
Optimization:- Distillation, pruning, caching, prompt compression, and how to make models affordable.
Agents:- Tool calling, memory, retries, failure modes, and why autonomous systems are chaos engines.
Security:- Prompt injection, data exfiltration, training data leaks, and tool misuse.
Deployment:- Model versioning, shadow runs, canaries, rollbacks, and killing bad models fast.
Distributed systems:- Queues, retries, idempotency, backpressure, and partial failures. ML is just distributed systems with gradients.
Documentation:- Model cards, data contracts, eval reports, and written tradeoffs.
Pick one stack. Build real systems. Break them. Fix them.
If I missed something, Add in the comment section.
The @FedEx call support number is the very stupid thing in place. It won’t even understand the specific concern and it won’t even be able to navigate the call to the human representative. It will have only some pre-fixed options feeder and won’t go beyond.
Worst customer support that was being provided by @airvistara and @united . I have a flight to US which is being operated by Vistara initially and then by United Airlines.
I have two basic questions for which none of the team’ have provided an answer.
#vistara#UnitedAirlines
Hey @elonmusk why aren’t you on LinkedIn? You could be a significant source for technical information when it comes to AI. You can spread your tech stuff there as well right? It can be more insightful.
#ElonMusk
May be certain users won’t feel much bad because iMessage is down. They will be more worse after knowing they didn’t get any text after it’s recovery.
#iMessage#sarcasm
As classes start in Jan, , we are much worried if we can make it for spring term.Since I am not opting for any defer, students like me are monitoring tirelessly to book the slots which are not abundantly available.
#moref1visaslots@USAndHyderabad@USAndMumbai@USAndChennai
Dear @USAndIndia
Can you please also tweet about when the F1 visa additional slots will be opened in bulk along with you regular tweets.
As many students are waiting for F1 to attend for the spring intake, it would be better if we have an update since it is already dec end.
Congratulations on a wonderful career @ImRaina . You can be very proud of your career. Hope that as Chinna Thala you keep entertaining in your yellow jersey. Wish you good luck in all that you do in the future.
Shri @PawanKalyan, your views about multifaceted education were taken into consideration while drafting the final #NEP2020.
Under NEP 2020, students will be given increased flexibility & choice of subjects to study so that they can design their own paths of study and life plans.
@ramjowrites garu your lyrics is awesome.
@sidsriram has given life to the song with @MusicThaman's music.
@MusicThaman bhayya nuvvu champesav ante music. Day by day your are giving your best. The way you have come back is literally applaudable.