A new analysis finds that AI companies now average just 40 out of 100 on transparency, marking a significant decline from last year.A new analysis finds that AI companies now average just 40 out of 100 on transparency, marking a significant decline from last year.Business[#item_full_content]
Earlier this month, Australia’s long-anticipated National AI Plan was released to a mixed reception.Earlier this month, Australia’s long-anticipated National AI Plan was released to a mixed reception.Business[#item_full_content]
Researchers at TU Wien have discovered an unexpected connection between two very different areas of artificial intelligence: Large Language Models (LLMs) can help solve logical problems—without actually “understanding” them.Researchers at TU Wien have discovered an unexpected connection between two very different areas of artificial intelligence: Large Language Models (LLMs) can help solve logical problems—without actually “understanding” them.Computer Sciences[#item_full_content]
Researchers at TU Wien have discovered an unexpected connection between two very different areas of artificial intelligence: Large Language Models (LLMs) can help solve logical problems—without actually “understanding” them.Researchers at TU Wien have discovered an unexpected connection between two very different areas of artificial intelligence: Large Language Models (LLMs) can help solve logical problems—without actually “understanding” them.[#item_full_content]
If you open a banking app, play a mobile game or scroll through a news feed every day while riding the bus, your commuting routine is probably bolstering your smartphone habit, according to new research that shows phone tendencies are stronger in locations chosen automatically.If you open a banking app, play a mobile game or scroll through a news feed every day while riding the bus, your commuting routine is probably bolstering your smartphone habit, according to new research that shows phone tendencies are stronger in locations chosen automatically.[#item_full_content]
In a study published in Frontiers in Science, scientists from Purdue University and the Georgia Institute of Technology outline practical approaches to overcome the limitations of modern computing hardware.In a study published in Frontiers in Science, scientists from Purdue University and the Georgia Institute of Technology outline practical approaches to overcome the limitations of modern computing hardware.Energy & Green Tech[#item_full_content]
Computer-aided design (CAD) systems are tried-and-true tools used to design many of the physical objects we use each day. But CAD software requires extensive expertise to master, and many tools incorporate such a high level of detail they don’t lend themselves to brainstorming or rapid prototyping.Computer-aided design (CAD) systems are tried-and-true tools used to design many of the physical objects we use each day. But CAD software requires extensive expertise to master, and many tools incorporate such a high level of detail they don’t lend themselves to brainstorming or rapid prototyping.[#item_full_content]
Computer-aided design (CAD) systems are tried-and-true tools used to design many of the physical objects we use each day. But CAD software requires extensive expertise to master, and many tools incorporate such a high level of detail they don’t lend themselves to brainstorming or rapid prototyping.Computer-aided design (CAD) systems are tried-and-true tools used to design many of the physical objects we use each day. But CAD software requires extensive expertise to master, and many tools incorporate such a high level of detail they don’t lend themselves to brainstorming or rapid prototyping.Robotics[#item_full_content]
When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm’s output matches reality. But according to new research, that tool may not be as reliable as many assume.When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm’s output matches reality. But according to new research, that tool may not be as reliable as many assume.Computer Sciences[#item_full_content]
When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm’s output matches reality. But according to new research, that tool may not be as reliable as many assume.When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm’s output matches reality. But according to new research, that tool may not be as reliable as many assume.[#item_full_content]
