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Asif Razzaq on Muck Rack

Asif Razzaq

Verified
(He/Him)
California, Los Angeles, Orange County, CA, San Jose
As seen in: Marktechpost, LinkedIn, Medium, Wiley Online Library, Elsevier, Frontiers, Flipboard, PRWeb, Business 2 Community, TechOhio, Business.com and
Covers:  Artificial Intelligence, Machine Learning, Data Science, Analytics, Deep Learning, Computer Vision, NLP, LLMs
Unleashing AI's potential. Editor and CEO at @marktechpost : AI News Platform with over 1.5 Million Visits per month

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Asif Razzaq’s Biography

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Asif Razzaq is an AI Journalist and Cofounder of Marktechpost AI Media Inc. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts over a mi…

Asif Razzaq’s Journalist Portfolio

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Microsoft AI Unveils 'TrOCR', An End-To-End Transformer-Based OCR Model For Text Recognition With...

Microsoft AI Unveils 'TrOCR', An End-To-End Transformer-Based OCR Model For Text Recognition With...

The problem of text recognition is a long-standing issue in document digitalization. Many current approaches …

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ByteDance Proposes 'DyStyle': A Novel Dynamic Neural Network For Style Editing

ByteDance Proposes 'DyStyle': A Novel Dynamic Neural Network For Style Editing

In the last few years, AI researchers have been using Generative adversarial networks (GANs) to create images…

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University of Oxford Researchers Release 'PASS' Dataset With 1.4M+ Images (Free From Humans) For ...

University of Oxford Researchers Release 'PASS' Dataset With 1.4M+ Images (Free From Humans) For ...

The development of modern machine learning could not have happened without an extensive research dataset. For…

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OpenAI's New Machine Learning Model Can Summarize Any Size Book with Human Feedback

OpenAI's New Machine Learning Model Can Summarize Any Size Book with Human Feedback

OpenAI has developed a new model to study the alignment problem of machine learning. This model can summarize…

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AI Research Group From NVIDIA Unveils An Advanced Framework To Estimate Physically Correct Human ...

AI Research Group From NVIDIA Unveils An Advanced Framework To Estimate Physically Correct Human ...

It is no secret that human motion synthesis has been a complex and, as of yet, unmet need. Existing technique…

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Too Much Thinking Can Break LLMs: Inverse Scaling in Test-Time Compute

Too Much Thinking Can Break LLMs: Inverse Scaling in Test-Time Compute

Discover why longer reasoning can harm large language models' accuracy and learn how to optimize their thinki…

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Articles

Perplexity Releases Hybrid Compute on Mac: Cloud Agents Orchestrate Down to a Local Model, Gated On Device

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By Asif Razzaq Verified
| Marktechpost Verified
Agentic assistants have a structural problem: the context that makes them useful — deal documents, privileged files, client records — is exactly the context users cannot send to a cloud endpoint. This week, Perplexity shipped its answer for Mac. Hybrid compute splits a single Perplexity Computer task between frontier models in the cloud and a compact model on the user’s Mac, with an on-device privacy gate deciding what may cross the boundary.
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Anthropic Releases Claude Fable 5.1 and Claude Mythos 5.1: 52.6% on Terminal-Bench-Science and 75% Cheaper Cache Reads

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By Asif Razzaq Verified
| Marktechpost Verified
Anthropic has released Claude Fable 5.1 and Claude Mythos 5.1, three months after the Fable 5 line shipped in June 2026. The two are the same underlying model behind different safeguard layers. Fable 5.1 is generally available as claude-fable-5-1; Mythos 5.1 stays restricted to vetted organizations. Both carry a 1M token context window and 128K max output tokens, with adaptive thinking always on.
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Researchers from Princeton, Ant Group and Stanford Introduce AQuA: A Two-Part Agentic Framework for Autonomous Factor Discovery and Model Development in Quantitative Finance

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By Asif Razzaq Verified
| Marktechpost Verified
Quantitative research agents that write their own experiments can corrupt the evidence they later learn from. A leaky feature that scores well gets stored as a successful precedent and propagated through later iterations. Prompt-level instructions and reviewer agents do not close this, because author and reviewer share the same blind spots. A team of researchers from Princeton University, Ant Group and Stanford University propose AQuA.
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Interview

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What was your first job as a journalist?

Marketing Associate at Epinex

What's your favorite social network?

Twitter

Who do you wish followed you?

Steve Jobs

Awards

'Influential Journalists in AI' by Onalytica

2021 - AI Journalism

'Influential Journalists in AI' by Onalytica 2021 highlights a selected list of journalists who work for, or contribute to well-known, global publications on the topic of AI. These people drive high authority and engagement on their social channels.

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The top 10 AI journalists in 2023- Muckrack

2023 - AI Journalism
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