Portrait of Ahmed Awadallah

Ahmed Awadallah

Partner Research Manager

News & features

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Microsoft Research Blog

| Arindam Mitra, Ahmed Awadallah, and Yash Lara

Orca-AgentInstruct, from Microsoft Research, can generate diverse, high-quality synthetic data at scale to post-train and fine-tune base LLMs for expanded capabilities, continual learning, and increased performance.

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Microsoft Research Blog

New Research | FLASH: Workflow automation agent for diagnosing recurring incidents; METAREFLECTION: Learning instructions for language agents using past reflections; Boosting LLM training efficiency through faster communication between GPUs; and more.

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Microsoft Research Blog

| Arindam Mitra, Hamed Khanpour, Corby Rosset, and Ahmed Awadallah

Microsoft’s Orca-Math, a specialized small language model, outperforms much larger models in solving math problems that require multi-step reasoning and shows the potential of using feedback to improve language models. Learn more.

MSR Podcast | AI Frontiers | Ahmed Awadallah
Microsoft Research Podcast

| Ahmed Awadallah and Ashley Llorens

What’s the driving force behind AI’s recent, rapid progress? Research manager Ahmed Awadallah shares his insights on this, the two-stage approach to training large-scale models, and the need for better model evaluation in this episode of the #MSRPodcast.

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Microsoft Research Blog

| Ahmed Awadallah

The release of OpenAI’s GPT-4 is a significant advance that builds on several years of rapid innovation in foundation models. GPT-4, which was trained on the Microsoft Azure AI supercomputer, has exhibited significantly improved abilities across many dimensions—from summarizing lengthy…

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Microsoft Research Blog

| Jianfeng Gao and Ahmed Awadallah

Recent progress in natural language understanding (NLU) has been driven in part by the availability of large-scale benchmarks that provide an environment for researchers to test and measure the performance of AI models. Most of these benchmarks are designed for…

An example of a multi-turn text-to-SQL task. The user query “Find the names of the top 3 highest sales books” corresponds to the formal program “SELECT title FROM book ORDER BY sale_amount DESC LIMIT 3”. The follow-up user query, “Who are their authors,” corresponds to the formal program “SELECT t1.title, t1.name FROM author AS t1 JOIN book AS t2 ON t1.id = t2.author_id ORDER BY t2.sale_amount DESC LIMIT 3”. In the corresponding database, there is an “Author” table with an “id” column, a “name” column, a “country” column, and an ellipsis signifying additional columns; a “Press” table with an “id” column, a “name” column, an “address” column, and an ellipsis signifying additional columns; and a “Book” table with an “id” column, a “title” column, an “author id” column, a “sale_amount” column, and an ellipsis signifying additional columns.
Microsoft Research Blog

| Alex Polozov, Chris Meek, and Ahmed Awadallah

One key aspiration of AI is to develop natural and effective task-oriented conversational systems. Task-oriented conversational systems use a natural language interface to collaborate with and support people in accomplishing specific goals and activities. They go beyond chitchat conversation. For…

Awards | British Computer Society

Ahmed Awadallah received the 2020 Karen Sparck Jones Award presented by the British Computer Society (BCS).  This award is given to researchers within 10 years of their PhD who have contributed significantly to information retrieval and/or natural language processing.

In the news | TheNextWeb

Researchers from the University of Washington and Microsoft’s AI team today unveiled a ‘Smart To-Do’ tool for automatically generating task lists from emails. Smart To-Do is an AI feature that scans your outgoing emails for actionable text and turns your…