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Logical soft tech Pvt.ldt
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PEwe make complex tech simple so you can understand the revolution in minutes 👍🏻
if you want content on a particular topic let us know in the comments
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follow or you may never see us again...
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#familyguy #thefamilyguy #explanation #explanations #techexplained #techniques #techrevolution #1967 #floppydisk #mos #dataprogramming #techhistory #innovation #technology #inventions #computerscience
@petercodelogic
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WEQLora:
Quantize the model during the fine-tuning process to use 8-bit precision instead of the typical 16 or 32-bit.
QLoRA is a more advanced approach that combines low-rank adaptation and quantization, making it ideal for fine-tuning on large models in resource-constrained environments.
@welcomeaiengineer
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SOAutomation testing demo. To enrol, Whatsapp as ‘Tosca’ to 9493400500 #softwarelyf #tosca #jobsearch
@softwarelyf
688.4K
SIDid you know about this GEM 💎??
100% Legit!
Enjoy
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@simplydigital.gr
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TEThree main sources of latency and methods to reduce it:
Latency from Model Size / Computation:
1. Use smaller or optimized models (distilled models, LoRA fine-tunes).
2. Apply quantization → compress weights (e.g., FP16 or INT8) to make the model faster.
3. Use model pruning → remove unnecessary neurons/connections without hurting accuracy much.
4. Enable batching → process multiple requests at once if the app allows.
Latency from Infrastructure / Bandwidth:
1. Run on GPUs or TPUs instead of CPUs for faster inference.
2. Deploy on specialized inference servers (like NVIDIA Triton, TensorRT, ONNX Runtime).
3. Scale horizontally → add more servers to handle high traffic without delays.
4. Optimize I/O pipelines → minimize time spent loading, decoding, or moving data between components.
Latency from Network Lag / Cloud Data Flow:
1. Use edge computing → run models closer to users (regional data centers, on-device).
2. Cache frequent or repeated responses locally so they don’t hit the server again.
3. Optimize API calls → avoid unnecessary back-and-forth between services.
Enable streaming responses (send partial outputs early, instead of waiting for the full result).
In short: shrink the model where possible, strengthen the infrastructure, and reduce unnecessary travel time for data. Together, these steps can bring latency down from seconds to milliseconds.
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🏷️ Day 45, 50 Day Challenge, Generative Al, Artificial Intelligence, Al, Large Language Models, OpenAl, Al Evolution, Important Concepts, Series, Al Series
@techwithnt
1.6K
CRLogical operators explained with examples
#btech #java #coding #interview #operatorsinjava
@creativekurrodu
73.3K
ACEric Schmidt sees systems AI as a game-changer—especially in solving the mystery of how AI models make decisions. He stresses the need for attributive models to explain AI behavior, citing self-driving cars that sometimes roll through stop signs without clear reasons or accountability.
He also highlights biology as the next frontier, where digitizing complex processes could unlock solutions to age-old problems.
With massive investment and experts shifting from physics and math to AI, Schmidt predicts breakthroughs in AI and biology within five years.
The future is being rewritten—are you ready to be part of it?
💬 What breakthrough do you think will happen first: smarter AI or digital biology?
FOLLOW @activeprogrammer to learn something new every day!
🎥: Stanford Graduate School of Business
#programmingfuture #aiandtech
#coderslife #machinelearningmodels
#futureofai
@activeprogrammer
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CHLG once staged a job interview with an unexpected twist.
Instead of a real window, the room featured an Ultra HD display showing a sudden meteor impact.
Believing the scene was real, candidates instinctively panicked — reacting exactly as they would to a real-world disaster.
The moment wasn’t accidental.
LG recorded the reactions to demonstrate just how realistic modern display technology can be when color accuracy, contrast, and resolution reach a certain level.
It proved that when visuals are precise enough, the human brain stops questioning what it sees.
A simple setup became a powerful demonstration of how screens can blur the line between digital and reality.
via : LGChile/YT
@check_blueprint
#lg #knowledge #technology #innovation #displaytech
@check_blueprint
613
PRManual testing starting to feel outdated? 🤖
A startup called BotGauge AI just raised $2M to bring AI agents into software testing. These bots explore apps, create their own test coverage, and even self-heal when UI changes break tests. No more fragile scripts or late-night alerts 🚨
Dream tool for QA… or a threat to testers?
Drop your thoughts below 💬
#itbootcamp #javascriptcourse #webdev #aicoding #itcareer
@procodingcom
367.8K
FLLearn control engineering from them
#engineering #robotics #engineer #tech #college #arduino #control #controlengineering #pid #controlsystem
@flywheelrobotics
40.1K
SECreo que, con tantos avances en IA, pasaremos de ser desarrolladores a convertirnos en orquestadores. Al final, nuestras líneas de código originales probablemente no lleguen ni al 20%. Pero esto no significa que nos vayamos a quedar sin trabajo; al contrario, estos avances nos permitirán evolucionar y mantenernos al día con la tecnología.
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#ia #chatgp #inteligenciaartificial #tecnología #avaces #desarrolladores #programadores serudda #programacion
@serudda
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