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  • React
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  • NextJS
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Fable 5 or GLM 5.2 ?

Pick between Fable 5 and GLM 5.2 and you're really picking between two things: reasoning power and cost at scale. Fable 5 wins the benchmarks for reasoning and coding. GLM 5.2 wins on price and carries a slightly larger context window, which makes it the sane default for high-volume work. Both are…
Thumbnail Image of Tutorial Fable 5 or GLM 5.2 ?
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Fine-Tuning LLMs Without Code Using Nvidia Spark

Watch: Fine-Tuning 8B Parameter Model Locally Demo with NVIDIA DGX Spark by NVIDIA Developer No-code fine-tuning on Nvidia Spark means using guided playbooks to train models locally instead of hand-wiring your own training environment. You bring data and pick a base model. Tools like NeMo AutoModel…
Thumbnail Image of Tutorial Fine-Tuning LLMs Without Code Using Nvidia Spark
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Fine-Tune a Learning Agent in Artificial Intelligence

Your dataset decides whether the fine-tune works or burns your budget. A small set of clean, consistent input-output pairs beats a giant noisy dump almost every time. FireAct is the proof point: fine-tuning Llama-2-7B on just 500 GPT-4 trajectories improved HotpotQA performance by 77%. High-signal…
Thumbnail Image of Tutorial Fine-Tune a Learning Agent in Artificial Intelligence
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Why AI Safety Exploits Fail in 2026

Most AI safety exploits fail in 2026 for one boring reason: the target stopped trusting the prompt. Real LLM applications now sit behind defensive perimeters that cut raw model output off from execution. With those perimeters live, an attacker has to defeat the entire system around the model. A…
Thumbnail Image of Tutorial Why AI Safety Exploits Fail in 2026
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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How to Keep AI Project Costs Low

AI costs come down to tokens, calls, and compute. The model you pick matters less than people think. The fastest way to spend less is to stop paying for work you don't need: bloated prompts, repeated calls, oversized context windows, and the retries that pile up quietly while you're not looking.…
Thumbnail Image of Tutorial How to Keep AI Project Costs Low
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
•Last Updated:
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