AI: From bench to bot
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This column by Tim Requarth explores the promises and pitfalls of artificial-intelligence tools in writing—when they can make writing better, faster and easier, and how to navigate the minefield of possible dangers.
Keeping it personal: How to preserve your voice when using AI
To harness the workmanlike prose of artificial intelligence while maintaining a recognizable style, use it as an analyzer rather than as a writer.
Keeping it personal: How to preserve your voice when using AI
To harness the workmanlike prose of artificial intelligence while maintaining a recognizable style, use it as an analyzer rather than as a writer.
From bench to bot: How important is prompt engineering?
To draft the most effective prompt, assume the stance of teacher.
From bench to bot: How important is prompt engineering?
To draft the most effective prompt, assume the stance of teacher.
From bench to bot: Does AI really make you a more efficient writer?
A more significant benefit may lie in improving quality, refining tone and reducing cognitive burden. But beware of bias.
From bench to bot: Does AI really make you a more efficient writer?
A more significant benefit may lie in improving quality, refining tone and reducing cognitive burden. But beware of bias.
From bench to bot: Boost your writing with AI personas
Asking ChatGPT to review your own grant proposals can help you spot weaknesses.
From bench to bot: Boost your writing with AI personas
Asking ChatGPT to review your own grant proposals can help you spot weaknesses.
From bench to bot: How to use AI to structure your writing
When given specific examples, ChatGPT can generate templates to help guide different types of documents.
From bench to bot: How to use AI to structure your writing
When given specific examples, ChatGPT can generate templates to help guide different types of documents.
From bench to bot: How to use AI tools to convert notes into a draft
ChatGPT can capitalize on the highly ordered nature of scientific writing to streamline your writing process.
From bench to bot: How to use AI tools to convert notes into a draft
ChatGPT can capitalize on the highly ordered nature of scientific writing to streamline your writing process.
From bench to bot: A scientist’s guide to AI-powered writing
I was initially skeptical of artificial-intelligence tools such as ChatGPT for scientific writing. But after months of using and teaching generative artificial intelligence, I have come to realize that it has a place in the scientific writer’s tool kit, even if it can’t write that grant for you from scratch.
From bench to bot: A scientist’s guide to AI-powered writing
I was initially skeptical of artificial-intelligence tools such as ChatGPT for scientific writing. But after months of using and teaching generative artificial intelligence, I have come to realize that it has a place in the scientific writer’s tool kit, even if it can’t write that grant for you from scratch.
Explore more from The Transmitter
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.