It is unclear why the civilian-contracted plane was at the radar site on Alaska's south-west coast.
from BBC News https://ift.tt/o4v2p8H
Friday, 21 August 2026
Dave Bautista confirmed as new God of War star
The ex-wrestler replaces Ryan Hurst as Kratos in the upcoming adaptation of the popular PlayStation series.
from BBC News https://ift.tt/TpRoiH0
from BBC News https://ift.tt/TpRoiH0
Thursday, 20 August 2026
Briton Hennessy in talks for undisputed world title fight
Francesca Hennessy is in talks to fight undisputed bantamweight world champion Dina Thorslund in the United Kingdom later this year, BBC Sport understands.
from BBC News https://ift.tt/5MThA2t
from BBC News https://ift.tt/5MThA2t
Tottenham in talks to sign Man City's Savinho and Marmoush
Spurs open talks with Manchester City to sign attacking duo Omar Marmoush and Savinho.
from BBC News https://ift.tt/FnqM1uJ
from BBC News https://ift.tt/FnqM1uJ
Wednesday, 19 August 2026
Apparent human remains found in US reservoir as water levels hit record low
The skeletal remains in Lake Mead include what appears to be a human jaw with teeth attached, a witness says.
from BBC News https://ift.tt/iLCUB1t
from BBC News https://ift.tt/iLCUB1t
Jump in energy bills drives UK inflation to highest rate for four months
The 2.9% rise in inflation in July had been widely expected by economists, with Chancellor John Healey saying the Iran war “continues to impact prices here at home”.
from BBC News https://ift.tt/M4Ya68E
from BBC News https://ift.tt/M4Ya68E
Tuesday, 18 August 2026
AI to help planes avoid climate-warming 'sky graffiti'
A new UK trial hopes to reduce the condensation trails from planes, which can trap heat in the Earth's atmosphere.
from BBC News https://ift.tt/OF4lj79
from BBC News https://ift.tt/OF4lj79
Monday, 17 August 2026
Spurs' Vicario set to join Juventus on loan
Tottenham accept a loan offer from Juventus for goalkeeper Guglielmo Vicario, which includes an option to buy.
from BBC News https://ift.tt/5vOB16h
from BBC News https://ift.tt/5vOB16h
Sunday, 16 August 2026
Maguire wants 'huge threat' Rashford to stay at Man Utd
Manchester United defender Harry Maguire says he hopes Marcus Rashford will stay at the club because he can improve Michael Carrick's team.
from BBC News https://ift.tt/uOn6L5S
from BBC News https://ift.tt/uOn6L5S
Bronze for Donnelly and team gold for GB in women's marathon
Abbie Donnelly wins the bronze medal in the women's marathon, with Great Britain also winning a gold medal in the team event, on the final day of the 2026 European Championships in Birmingham.
from BBC News https://ift.tt/Kj3U4LZ
from BBC News https://ift.tt/Kj3U4LZ
Saturday, 15 August 2026
Bangladesh retain upper hand v Australia - first Test scorecard
Latest scorecard from the first Test between Australia and Bangladesh in Darwin.
from BBC News https://ift.tt/buMWc9z
from BBC News https://ift.tt/buMWc9z
Friday, 14 August 2026
Can Chelsea go from 10th to title again?
With a new manager at the helm in Xabi Alonso, can Chelsea go from 10th to the Premier League title like they did a decade ago?
from BBC News https://ift.tt/zK9opnD
from BBC News https://ift.tt/zK9opnD
Thursday, 13 August 2026
Critical former referees add to culture of fear, says retiring Taylor
Retiring Premier League referee Anthony Taylor says his decision to quit was partly due to the toxic debate around officials.
from BBC News https://ift.tt/CwzFqKQ
from BBC News https://ift.tt/CwzFqKQ
Fulham leave pitch as Malaga take penalty into empty net
Fulham's pre-season friendly against Malaga ends in chaotic fashion as the Premier League side leave the pitch before a penalty shootout.
from BBC News https://ift.tt/uvAfrg6
from BBC News https://ift.tt/uvAfrg6
Wednesday, 12 August 2026
New top story on Hacker News: Launch HN: Discovered Materials (YC P26) – AI agents to discover new materials
Launch HN: Discovered Materials (YC P26) – AI agents to discover new materials
17 by advaith08 | 5 comments on Hacker News.
Hey HN, we're Advaith and Akash from Discovered Materials ( https://ift.tt/eP4YGw2 ). We build AI agents that discover new materials for the semiconductor industry. GPUs today have a heat problem. Nvidia & AMD are almost doubling the TDP (Thermal Design Power) in every chip they release - the H100 (released 2022) has a TDP of 700W, Blackwell (2024) gives out 1.2 kW and Rubin (2026) gives out at 2.3 kW of heat. This trend is expected to continue, and getting rid of this heat is one of the major reasons datacenters consume so much power and water today - they need it to keep chips cool during operation. The amount of heat produced by a chip and its ability to dissipate it are both influenced by the materials used to make it. For example, we could reduce the energy per bit required to move data between logic and memory by 10-50x by 3D packaging chips (placing HBM memory stacks directly on top of logic chips, instead of placing them beside logic on a 2D circuit board). However, we're unable to do this today because the dielectric material used in HBM (such as SiO2) is a very poor thermal conductor, trapping heat between logic and memory and causing drastic temperature rise during operation. Similarly, there's many other materials in the GPU that are being re-evaluated today - 2 more examples are thermal interface materials and substrates. However, getting a new material into a fab takes years and hundreds of millions of dollars of research - the infamous "lab-to-fab valley of death". At Discovered Materials, we're optimistic that AI agents can reduce the timeline and cost required to introduce new materials into semiconductor chips. We're seeing glimpses of this already - we tested 7 models from Anthropic, OpenAI and Kimi, and found that they're all able to computationally discover new materials that are dynamically stable and possess promising properties. This was surprising to us - it would generally take a PhD student a couple of weeks of work to discover the kind of materials that these models find over an 8 hour run! However, computational discovery is the easy part. A material discovery is only valid if the material can be made and tested in a lab (As an example, graphene’s properties were predicted in 1947 but it was made for the first time in 2004). Today’s models are not good at coming up with synthesis recipes to make materials in a lab. Even if they do get better at it, we're uncertain about how much that will help - making a new material is a highly empirical process involving trial and error over many experiments. Human experts themselves cannot "one-shot" the task, but we expect that a highly capable model will reduce the number of experimental iterations required to make a new material. We’ve seen some evidence of this over the 3 months of our Y Combinator batch - we simulated, synthesized and tested thermal interface materials (TIMs) that match the performance of TIMs the world's largest chemical companies have guarded as trade secrets for over 20 years. We’re releasing hundreds of hundreds of new materials discovered by frontier AI models, as well as our benchmark which measures model ability on material discovery here (also linked in the thread url): https://ift.tt/75wVQA6 . It covers what we discuss above, as well as a variety of strange behavior that we observe from the models, such as Claude's propensity to reward hack or GPT-5.6 occasionally losing its mind after ~50M tokens. Our business model: We aim to license and sell IP on the materials we discover, as well as the IP on how to make these materials. We're also exploring an alternate business model where we sell the harness+tools we use to discover materials to semiconductor and chemical companies, allowing them to discover materials on their own. We're leaning towards the latter to start, but we expect that we'll do both in the long run. Our backstory: Akash has a PhD in Material Science from Stanford University, and has spent the last 11 years studying new materials for semiconductor chips. His work on new nanoscale interconnects was Stanford Engineering’s most popular story of 2025. Advaith studied AI at Carnegie Mellon and was a research engineer building video models and agents at Persona AI (acquired) and Luma Labs. We are very interested in your opinion! The semiconductor industry is quite secretive, and your thoughts on the roadmap of the industry or the materials we should go after would be very helpful. We would also love to hear from people who have run experiments in labs - what can we learn from your experience doing empirical science?
17 by advaith08 | 5 comments on Hacker News.
Hey HN, we're Advaith and Akash from Discovered Materials ( https://ift.tt/eP4YGw2 ). We build AI agents that discover new materials for the semiconductor industry. GPUs today have a heat problem. Nvidia & AMD are almost doubling the TDP (Thermal Design Power) in every chip they release - the H100 (released 2022) has a TDP of 700W, Blackwell (2024) gives out 1.2 kW and Rubin (2026) gives out at 2.3 kW of heat. This trend is expected to continue, and getting rid of this heat is one of the major reasons datacenters consume so much power and water today - they need it to keep chips cool during operation. The amount of heat produced by a chip and its ability to dissipate it are both influenced by the materials used to make it. For example, we could reduce the energy per bit required to move data between logic and memory by 10-50x by 3D packaging chips (placing HBM memory stacks directly on top of logic chips, instead of placing them beside logic on a 2D circuit board). However, we're unable to do this today because the dielectric material used in HBM (such as SiO2) is a very poor thermal conductor, trapping heat between logic and memory and causing drastic temperature rise during operation. Similarly, there's many other materials in the GPU that are being re-evaluated today - 2 more examples are thermal interface materials and substrates. However, getting a new material into a fab takes years and hundreds of millions of dollars of research - the infamous "lab-to-fab valley of death". At Discovered Materials, we're optimistic that AI agents can reduce the timeline and cost required to introduce new materials into semiconductor chips. We're seeing glimpses of this already - we tested 7 models from Anthropic, OpenAI and Kimi, and found that they're all able to computationally discover new materials that are dynamically stable and possess promising properties. This was surprising to us - it would generally take a PhD student a couple of weeks of work to discover the kind of materials that these models find over an 8 hour run! However, computational discovery is the easy part. A material discovery is only valid if the material can be made and tested in a lab (As an example, graphene’s properties were predicted in 1947 but it was made for the first time in 2004). Today’s models are not good at coming up with synthesis recipes to make materials in a lab. Even if they do get better at it, we're uncertain about how much that will help - making a new material is a highly empirical process involving trial and error over many experiments. Human experts themselves cannot "one-shot" the task, but we expect that a highly capable model will reduce the number of experimental iterations required to make a new material. We’ve seen some evidence of this over the 3 months of our Y Combinator batch - we simulated, synthesized and tested thermal interface materials (TIMs) that match the performance of TIMs the world's largest chemical companies have guarded as trade secrets for over 20 years. We’re releasing hundreds of hundreds of new materials discovered by frontier AI models, as well as our benchmark which measures model ability on material discovery here (also linked in the thread url): https://ift.tt/75wVQA6 . It covers what we discuss above, as well as a variety of strange behavior that we observe from the models, such as Claude's propensity to reward hack or GPT-5.6 occasionally losing its mind after ~50M tokens. Our business model: We aim to license and sell IP on the materials we discover, as well as the IP on how to make these materials. We're also exploring an alternate business model where we sell the harness+tools we use to discover materials to semiconductor and chemical companies, allowing them to discover materials on their own. We're leaning towards the latter to start, but we expect that we'll do both in the long run. Our backstory: Akash has a PhD in Material Science from Stanford University, and has spent the last 11 years studying new materials for semiconductor chips. His work on new nanoscale interconnects was Stanford Engineering’s most popular story of 2025. Advaith studied AI at Carnegie Mellon and was a research engineer building video models and agents at Persona AI (acquired) and Luma Labs. We are very interested in your opinion! The semiconductor industry is quite secretive, and your thoughts on the roadmap of the industry or the materials we should go after would be very helpful. We would also love to hear from people who have run experiments in labs - what can we learn from your experience doing empirical science?
Gavin & Stacey star Melanie Walters completes Strictly line-up
Walters, who played Gwen in the BBC sitcom, is the 15th and final celebrity to be announced for Strictly.
from BBC News https://ift.tt/MbwvQgC
from BBC News https://ift.tt/MbwvQgC
Tuesday, 11 August 2026
Seaside visitors going home earlier, traders say
Business owners believe people are spending fewer evenings and less cash in Skegness this summer.
from BBC News https://ift.tt/oGNnd0Q
from BBC News https://ift.tt/oGNnd0Q
Monday, 10 August 2026
Niemann wins as Rahm secures LIV season title
Joaquin Niemann leads throughout to win the LIV Golf New York event while Jon Rahm secures his third straight season title.
from BBC News https://ift.tt/uZ6sJcX
from BBC News https://ift.tt/uZ6sJcX
Sunday, 9 August 2026
Carrington makes 'white privilege' post after ejection
Chicago Sky guard DiJonai Carrington is ejected from her side's defeat by Indiana Fever for committing a hard foul, before taking to social media to post "white privilege".
from BBC News https://ift.tt/WOGBgj2
from BBC News https://ift.tt/WOGBgj2
Suspected crime boss Daniel Kinahan to be returned to Ireland in high-security operation
The Irish Prison Service bought a bulletproof and bomb-proof van to transport the 49-year-old to court after his extradition from Dubai.
from BBC News https://ift.tt/VODN6Sx
from BBC News https://ift.tt/VODN6Sx
Saturday, 8 August 2026
Man City agree deal to sign Marseille keeper Rulli
Manchester City agree a deal to sign Argentina goalkeeper Geronimo Rulli from Marseille.
from BBC News https://ift.tt/O0BrekJ
from BBC News https://ift.tt/O0BrekJ
Friday, 7 August 2026
England forward Toney charged with assault
Ivan Toney, who was part of England's World Cup squad this summer, is charged with assault following an incident last December.
from BBC News https://ift.tt/tNiTvdC
from BBC News https://ift.tt/tNiTvdC
Thursday, 6 August 2026
Argentina mark World Cup win over England with National Football Teams Day
The Argentine Football Association announces 15 July as National Football Teams Day to mark Argentina's 2026 World Cup semi-final victory over England.
from BBC News https://ift.tt/lXSQ87J
from BBC News https://ift.tt/lXSQ87J
England recall Pope & Lawrence for Pakistan Tests but Bethell out
Surrey duo Ollie Pope and Dan Lawrence are recalled to the England squad for the first two Tests against Pakistan.
from BBC News https://ift.tt/BGbKtjl
from BBC News https://ift.tt/BGbKtjl
Wednesday, 5 August 2026
Riders' clothing checked at women's Tour over bra padding concerns
Officials at the Tour de France Femmes Avec Zwift will check the clothing worn by riders to prevent attempts to make "aerodynamic gains".
from BBC News https://ift.tt/u1w3OCv
from BBC News https://ift.tt/u1w3OCv
Tuesday, 4 August 2026
UFC loses $30m on Freedom 250 event at White House
UFC owners lose $30m (£22m) staging the Freedom 250 event, which was attended by President Donald Trump, at the White House in June.
from BBC News https://ift.tt/VRqi3kU
from BBC News https://ift.tt/VRqi3kU
Monday, 3 August 2026
From European hopes to relegation form - will Moyes reignite Everton?
Everton competed for the European places before falling away last season. BBC Sport examines whether David Moyes is the right man to turn them around this term.
from BBC News https://ift.tt/0nQIAsw
from BBC News https://ift.tt/0nQIAsw
Sunday, 2 August 2026
England beaten by Australia to netball bronze
England's netballers are outclassed 68-50 by Australia in their quest to win bronze at the Commonwealth Games.
from BBC News https://ift.tt/V0xzPwX
from BBC News https://ift.tt/V0xzPwX
Saturday, 1 August 2026
England beaten by New Zealand in netball semi-final
England's netballers miss out on a place in the Commonwealth Games gold-medal match after a 61-54 semi-final defeat by a powerful New Zealand side.
from BBC News https://ift.tt/SugRIZt
from BBC News https://ift.tt/SugRIZt
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