Dragonfly's Titan Landing: NASA's Quest to Unravel the Mysteries of the Saturnian Moon

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Stuart Gary: This is space time series 29 episode

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117 full broadcast on 30

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September 2026 coming up on Space

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Time, NASA names Dragonfly's

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landing site on the saturnian moon Titan.

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New clues about the Earth's moon's ancient

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magnetic field and why galaxies in the

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early universe look so weird.

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All that and more coming up on, um, Space

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Time. Welcome to

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Space Time with Stuart G.

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NASA has identified the landing site where

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its Dragonfly rotocopter, uh, will first

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touch down on the surface of the saturnian

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moon Titan. The target area

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comprises a large dune field with some inter

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dune terrain south of Silic Crater and

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stretches along the edge of a range of

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mountains or hills. The International

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Astronomical Union, the global body

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responsible for officially designating

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objects in space, has approved naming the

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region Amakik uh Andai. First part of

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the name is Mayan people appealed to the

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spirit Amakaq to stop strong winds from

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damaging their crops. The name literally

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translates into the one who locks up the

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wind. An ande aligns with the International

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Astronomical Union's convention of naming

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dune fields in Latin after gods and goddesses

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of wind. Meanwhile, construction work

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continues on the Dragonfly spacecraft itself,

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which is now being assembled in a clean room

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at the Johns Hopkins Applied Physics

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Laboratory in Lorell, Maryland. Cables are

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being carefully installed in the flight

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fuselage, providing the Titan bound

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rotorcraft with its central nervous system

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now. Ah. Collectively, these bundles of

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wires, cables and connectors make up the

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spacecraft's electrical harness, which will

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transmit power and data between the lander's

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computers, actuators, sensors, scientific

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instruments and battery. Dragonfly

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lander harness lead Jacqui Perry says it's a

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key milestone for the engineers and

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technicians building the vehicle. The wire is

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silver coated copper, insulated with a heat

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resistant durable polymer coating and then

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wrapped in aluminium, which is then attached

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at plastic and metal connectors.

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Perry says the wiring harness could only be

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installed once the flight structure was

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delivered and the remote interface units and

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temperature sensors were installed. The

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harness is typically one of the first

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components delivered to a spacecraft.

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Dragonfly passed its critical design review

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in 2022. Fabrication of the vehicle began

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in late 2024 and finished last year.

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Dragonfly is slated for launch in 2028 and

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will reach the Saturnian moon in late 2034.

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Dragonfly's operating environment on Titan

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poses some unique challenges because of the

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rotorcraft's thermos bottle design. Insulated

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to retain heat from its nuclear power source

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so it can stay warm in Titan's extremely cold

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conditions, the harness had been designed to

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route under a lay foam insulation on the

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outside of the lander and accommodate the

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circulation of warm air through the inside.

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Perry says the rotorcraft's high power

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demands require both 4 and 8Ah gauge

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wire, yet the harness still had to be

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flexible enough to weave through the packed

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interior, which includes the flight systems

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and instrument boxes as well as the 136

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kilogramme battery. Dragonfly

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will investigate Titan's prebiotic chemistry

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and assess the moon's habitability. It's not

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primarily a life detection mission, but aims

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to study how far organic chemistry has

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progressed in an environment rich in carbon

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compounds, which includes possible past

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mixing of liquid water and organics. The

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car sized 875 kilogramme lander

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features twin quadrotor engines powered by a

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radioisotope thermoelectric generator

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providing electricity and heat. The

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3.85 metre long vehicle is designed to

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fly several kilometres between landing sites,

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allowing it to sample diverse locations.

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Mission managers expect to cover over 115

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kilometres during Dragonfly's 3.3 year

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primary mission, exploring a range of

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different environments from organic dunes to

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deposits associated with an impact crater.

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Silk Crater, which we mentioned earlier,

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where liquid water and complex organic

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materials, which are key to life as we know

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it, once existed together. Scientific

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analysis indicates the impact that formed

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Silk Crater melted the icy bedrock,

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potentially creating a large temporary pool

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of water that could have remained liquid for

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hundreds of thousands of years under an

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insulating ice layer like winter ponds on the

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Earth.

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This report from NASA TV

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Saturn's largest

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NASA TV: moon, Titan, has a thick atmosphere and a

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frozen surface rich in organic molecules.

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In 2034, a NASA mission called

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Dragonfly will arrive at Titan and study its

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chemical makeup. Dragonfly is a

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rotorcraft designed to visit multiple sites

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across the moon's varied terrain.

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At each new landing site on Titan's surface,

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Dragonfly uses a pulsed neutron generator

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and onboard gamma ray sensor to detect key

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elements such as carbon and hydrogen in

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organic materials or oxygen in water

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ice. Dragonfly determines if there are

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well defined layers of these materials just

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below the lander for a closer inspection.

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Dragonfly uses its drill to generate

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tailings from Titan's hard frozen surface.

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These surface samples can then be ingested

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through the pneumatic system carried with

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Titan air into the chilled sample lines into

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the sample collection carousel. One of the

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carousel sample cups is placed in a pneumatic

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port. The cup captures the surface

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material from the cold air stream and

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transfers it to the chemical laboratory for

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measurement. Pulses from a laser

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release large organic molecules from the

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surface sample for analysis in the Mass

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spectrometer. The mass spectrometer sorts

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molecules by mass and measures diagnostic

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fragments that tell Dragonfly the kinds of

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chemical components that are present in the

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surface and whether there are molecules of

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prebiotic interest. For those

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potential prebiotic samples, a new cup is

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placed into an oven and heated to release

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molecules into a gas chromatograph, where

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they are sorted for size and type before

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entering the mass spectrometer. This

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advanced separation of organic components

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includes isolating molecules with the same

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formula but different chiral arrangements, or

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handedness.

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Having a preference for one handedness over

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another is a key biosignature for life on

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Earth. When the chemical analysis is

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complete, Dragonfly may choose to take

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another surface sample or find a new location

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on Titan to investigate.

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Stuart Gary: This whole mission's quite a challenge. Titan

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is unique in our solar system. It has a

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diameter of 5,150 kilometres,

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making it Saturn's largest moon and 50%

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bigger than the Earth's moon. In fact, it's

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larger than the planet Mercury. It's also the

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only moon with a substantial atmosphere and

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the only world other than Earth where clouds

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release rain that form streams and rivers,

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which then flow into lakes and seas.

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But Titan is so cold, the water there is

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normally frozen solid, forming bedrock. And

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instead of water, the liquid rain on Titan is

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made up of methane and ethane hydrocarbons.

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But scientists describe Titan as analogous to

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the early Earth. That's because it preserves

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a set of environmental and chemical

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conditions which are thought to have existed

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on our planet billions of years ago, before

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life arose and before free oxygen

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accumulated in our atmosphere. It

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therefore serves as a natural laboratory for

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studying prebiotic chemistry on a planetary

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scale. Scientists think its complex organic

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chemistry, methane cycle and possible

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environments could support exotic forms of

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life, or at least prebiotic chemistry.

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It's also considered one of the more feasible

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destinations for future human exploration

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among the outer solar system bodies due to

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its thick atmosphere for radiation shielding

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and available resources.

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Titan was extensively studied by the Cassini

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Huygens mission, which orbited the Saturnian

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system between 2004 and 2017.

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The Huygens Lander was deployed from the

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Cassini spacecraft down to Titan's surface on

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December 25, 2004, landing

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on January 14, 2005, near the

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Ediri region, the boundary between brighter

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highlands and darker plains. The lander

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spent about 90 minutes on the surface taking

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readings and measurements before the

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batteries ran out. Huygens was able to

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confirm that Titan has a thick, nitrogen

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dominated atmosphere with methane and a range

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of aerosols and complex organic chemistry.

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It measured strong High altitude zonal winds

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on its way down and weaker winds near the

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surface. It also measured a surface

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temperature of -179 degrees Celsius

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and a surface atmospheric pressure about 50%

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higher than sea level here on Earth.

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Intriguingly, it found the ground on Titan

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was soft and damp, with the consistency of

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wet sand, clay or lightly packed snow.

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Images showed the surface of Titan was

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littered with water ice, pebbles or cobbles a

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few centimetres across on an orange tinted

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organic rich plane. There was also evidence

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of past liquid flows near the landing site

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and possible methane release from the

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subsurface. Needless to say, as the

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Dragonfly mission progresses, we'll keep you

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informed. This is space

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time.

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Still to come, new clues about the Earth's

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Moon's ancient magnetic field. And we examine

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why galaxies in the early universe look so

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weird. All that and more still to come

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on space time.

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A new study claims that just like the present

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day Earth, our moon once had a geodynamo

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driven magnetic field. On Earth, the

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movement of liquid iron in the planet's outer

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core generates its global magnetic field.

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This so called geodynamo works on a similar

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principle to a dynamo on a bicycle, which

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converts mechanical motion into electrical

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energy. But unlike today's Earth, the Moon

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no longer has a core generated magnetic

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field. One of the study's authors, Anna

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Mittelholz from EDH Zurich, says there's a

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heated ongoing debate about whether the Moon

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also operated a dynamo in the past.

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That's because analysis of rock samples

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brought back to Earth by the Apollo

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astronauts are somewhat contradictory. Some

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researchers assume there was a strong

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magnetic field that existed over a long

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period of time, somewhere around 4.25 to

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3.5 billion years ago, while others find

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absolutely no evidence of this. You see, in

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addition to the dynamo theory, there's a

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second possible explanation for the

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magnetised lunar rocks, namely impacts from

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massive meteorites or asteroids, which could

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have triggered a, uh, magnetization process

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on the Moon. But the new research

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reported in the journal Science Advances now

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supports the dynamo theory. Mittelholz and

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colleagues say that around 4.2 billion years

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ago, the Moon did indeed possess an

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internally generated magnetic field. Uh, now

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this claim isn't based on rock samples, but

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on data collected by probes in lunar orbit,

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including gravity measurements by NASA's

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GRAIL probes and magnetic field models.

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Drawing on orbital measurements from the

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Lunar Prospector, UH and Kagua missions

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to reach their conclusions, the authors

270
00:11:28.230 --> 00:11:30.550
examined the Dewa region on the lunar far

271
00:11:30.550 --> 00:11:32.430
side, which is never seen from Earth.

272
00:11:32.910 --> 00:11:35.150
Mittelholz says Dewa has one of the strongest

273
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magnetic field anomalies on the far side of

274
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the Moon. And a distinct gravity anomaly

275
00:11:39.390 --> 00:11:42.270
coincides spatially there as well as that

276
00:11:42.270 --> 00:11:44.110
means this region contains rocks that were

277
00:11:44.110 --> 00:11:46.070
more strongly magnetised, while at the same

278
00:11:46.070 --> 00:11:49.070
time denser than elsewhere. In most cases,

279
00:11:49.150 --> 00:11:51.190
the origin of magnetic anomalies measured

280
00:11:51.190 --> 00:11:54.150
from lunar orbits are known. But the gravity

281
00:11:54.150 --> 00:11:56.630
data gives scientists an insight into the

282
00:11:56.630 --> 00:11:58.830
density and consequently the type of material

283
00:11:58.830 --> 00:12:01.590
beneath the surface. Mittelholz says where

284
00:12:01.590 --> 00:12:03.230
the magnetic field and gravity signals

285
00:12:03.230 --> 00:12:05.950
coincide, it is possible to combine the two

286
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and attribute the anomaly to a specific

287
00:12:07.910 --> 00:12:10.730
geological feature. And that's where Dewar

288
00:12:10.730 --> 00:12:13.250
comes in. It allowed the authors to create an

289
00:12:13.250 --> 00:12:15.930
accurate model of the subsurface by jointly

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00:12:15.930 --> 00:12:18.120
processing gravity and magnetic field data.

291
00:12:18.120 --> 00:12:20.690
Uh, this data shows the area beneath

292
00:12:20.690 --> 00:12:23.010
Dewar's surface contains a rock body

293
00:12:23.010 --> 00:12:25.290
approximately 60 kilometres wide, extending

294
00:12:25.290 --> 00:12:27.290
to a depth of around nine kilometres.

295
00:12:27.850 --> 00:12:30.250
It's far denser than the surrounding crust

296
00:12:30.250 --> 00:12:33.250
and it's strongly magnetised. Combined with

297
00:12:33.250 --> 00:12:35.130
a surface geochemistry and an arch

298
00:12:35.130 --> 00:12:37.050
topography, the authors conclude that it

299
00:12:37.050 --> 00:12:39.290
solidified magma that's risen from deep

300
00:12:39.290 --> 00:12:41.990
below, part of a buried volcanic complex.

301
00:12:42.550 --> 00:12:45.190
The age of the structure, 4.2 billion years,

302
00:12:45.190 --> 00:12:47.270
was determined from various deposits of

303
00:12:47.270 --> 00:12:49.270
impact material on the lunar surface.

304
00:12:49.830 --> 00:12:51.950
Betelholz says because they know how much

305
00:12:51.950 --> 00:12:54.190
iron is present in such a rocky body, they

306
00:12:54.190 --> 00:12:55.790
can estimate the minimum strength the

307
00:12:55.790 --> 00:12:57.790
magnetic field must have had as the magma

308
00:12:57.790 --> 00:13:00.590
slowly cooled. It shows that at the time, the

309
00:13:00.590 --> 00:13:02.550
magnetic field on the Moon was likely more

310
00:13:02.550 --> 00:13:05.430
than 10 micro Tesla. Now, by comparison,

311
00:13:05.430 --> 00:13:07.390
here on Earth today, the planet's magnetic

312
00:13:07.390 --> 00:13:10.350
field stands at around 50 micro Tesla. The

313
00:13:10.350 --> 00:13:12.230
authors have ruled out the possibility of an

314
00:13:12.230 --> 00:13:14.230
impact crater creating the magnetic field.

315
00:13:14.230 --> 00:13:16.550
Because there's no matching cratering signs,

316
00:13:17.030 --> 00:13:19.670
it's still unclear how the small lunar core

317
00:13:19.670 --> 00:13:21.670
could have generated such a strong magnetic

318
00:13:21.670 --> 00:13:24.270
field. So the authors admit the existence of

319
00:13:24.270 --> 00:13:26.870
an early lunar geodynamo isn't yet fully

320
00:13:26.870 --> 00:13:29.550
resolved. This study is also

321
00:13:29.550 --> 00:13:31.350
providing fresh insights into another

322
00:13:31.350 --> 00:13:33.670
puzzling phenomena lunar swirls.

323
00:13:34.150 --> 00:13:36.590
These bright, curved and striped patterns on

324
00:13:36.590 --> 00:13:38.990
the Moon's surface stand out clearly against

325
00:13:38.990 --> 00:13:41.860
their darker surroundings. Wherever such

326
00:13:41.860 --> 00:13:44.340
swirl patterns appear, scientists always find

327
00:13:44.340 --> 00:13:47.300
magnetic anomalies. And there is a lunar

328
00:13:47.300 --> 00:13:49.340
swirl on the surface of the Dewar region,

329
00:13:49.420 --> 00:13:52.260
right above the observed anomaly. The origin

330
00:13:52.260 --> 00:13:55.020
of the swirls remains a matter of debate. One

331
00:13:55.020 --> 00:13:57.260
possible explanation is that the swirls only

332
00:13:57.340 --> 00:13:59.060
form where the magnetic field runs

333
00:13:59.060 --> 00:14:01.220
horizontally at the surface. As is the case

334
00:14:01.220 --> 00:14:03.980
with the Dewar swirl, the horizontal field

335
00:14:03.980 --> 00:14:06.260
deflects the solar wind, thereby protecting

336
00:14:06.260 --> 00:14:08.470
the surface from weathering. And as a result,

337
00:14:08.550 --> 00:14:10.390
the area remains brighter than its

338
00:14:10.390 --> 00:14:12.990
surroundings, Mittelholz says That would be

339
00:14:12.990 --> 00:14:15.270
important information for future astronauts,

340
00:14:15.270 --> 00:14:17.070
as magnetic field lines could offer

341
00:14:17.070 --> 00:14:19.150
protection from the solar wind, and the

342
00:14:19.150 --> 00:14:21.630
swirls would indicate the locations of that

343
00:14:21.630 --> 00:14:24.310
shielding. This is space time.

344
00:14:25.030 --> 00:14:27.230
Still to come. Why galaxies in the early

345
00:14:27.230 --> 00:14:29.390
universe look so weird? And later in the

346
00:14:29.390 --> 00:14:31.670
Science report, discovery of a common

347
00:14:31.670 --> 00:14:33.990
chemical in plastics, which has been linked

348
00:14:33.990 --> 00:14:36.550
to the development of ADHD and autism.

349
00:14:37.120 --> 00:14:39.440
All that and more still to come on, uh, space

350
00:14:39.520 --> 00:14:39.920
time.

351
00:14:55.520 --> 00:14:57.960
A new study suggests that the first galaxies

352
00:14:57.960 --> 00:14:59.760
in the universe looked a bit weird because

353
00:14:59.760 --> 00:15:02.320
their stars generated weaker stellar winds

354
00:15:02.610 --> 00:15:05.170
compared to those we see today. The new

355
00:15:05.170 --> 00:15:06.810
research could reshape science's

356
00:15:06.810 --> 00:15:09.050
understanding of how galaxies formed in the

357
00:15:09.050 --> 00:15:12.010
early universe. The findings reported in the

358
00:15:12.010 --> 00:15:14.090
Astrophysical Journal are showing that the

359
00:15:14.090 --> 00:15:16.130
more astronomers learn about the universe's

360
00:15:16.130 --> 00:15:18.370
earliest galaxies, the stranger they seem.

361
00:15:19.010 --> 00:15:21.570
The new observations are based on a survey by

362
00:15:21.570 --> 00:15:23.730
NASA's Hubble Space Telescope, which looked

363
00:15:23.730 --> 00:15:26.650
at 29 massive stars located in extremely

364
00:15:26.650 --> 00:15:28.810
metal pore galaxies, finding they all had

365
00:15:28.810 --> 00:15:30.930
unexpectedly weak stellar winds.

366
00:15:31.820 --> 00:15:34.140
Astronomers use the term metals to describe

367
00:15:34.140 --> 00:15:36.180
all elements heavier than hydrogen and

368
00:15:36.180 --> 00:15:39.060
helium. The treasury of Extremely

369
00:15:39.060 --> 00:15:41.980
Metal Poor O Stars, or TEMPOS survey, uses

370
00:15:41.980 --> 00:15:44.340
ultraviolet observations from Hubble's Cosmic

371
00:15:44.340 --> 00:15:47.100
Origin Spectrograph to study massive stars in

372
00:15:47.100 --> 00:15:49.180
nearby galaxies, which are the best available

373
00:15:49.180 --> 00:15:51.340
analogues for stars in the early universe.

374
00:15:51.660 --> 00:15:54.020
The TEMPOS dataset could help astronomers

375
00:15:54.020 --> 00:15:56.300
build better models of massive stars in order

376
00:15:56.300 --> 00:15:58.420
to understand how they shaped galaxies when

377
00:15:58.420 --> 00:16:01.270
the universe was still very young. And these

378
00:16:01.270 --> 00:16:03.110
models would be essential for interpreting

379
00:16:03.110 --> 00:16:05.350
the observations of early galaxies now coming

380
00:16:05.350 --> 00:16:07.310
to light. Thanks to NASA's Webb Space

381
00:16:07.310 --> 00:16:10.110
Telescope studies. Lead author

382
00:16:10.110 --> 00:16:12.430
Grace Telford from the University of Utah

383
00:16:12.430 --> 00:16:14.790
says Webb is opening up a whole new slew of

384
00:16:14.790 --> 00:16:16.990
questions about the evolution of these early

385
00:16:16.990 --> 00:16:19.710
weird galaxies. Tilford says the

386
00:16:19.710 --> 00:16:22.110
scientific motivation behind TEMPOS is to

387
00:16:22.110 --> 00:16:23.990
help understand what's going on in these

388
00:16:23.990 --> 00:16:26.910
early galaxies. Massive stars, those with

389
00:16:26.910 --> 00:16:28.710
masses more than 10 times greater than our

390
00:16:28.710 --> 00:16:31.510
sun, are rare but powerful engines of cosm.

391
00:16:32.730 --> 00:16:35.290
They produce intense radiation. They shed

392
00:16:35.290 --> 00:16:37.370
materials through powerful stellar winds,

393
00:16:37.370 --> 00:16:40.170
they burn very hot, very bright, and very

394
00:16:40.250 --> 00:16:43.170
fast, and end their short lives as supernova

395
00:16:43.170 --> 00:16:45.650
explosions, blasting vast amounts of energy

396
00:16:45.650 --> 00:16:47.770
and material into the surrounding space.

397
00:16:48.490 --> 00:16:50.450
Consequently, they govern the evolution of

398
00:16:50.450 --> 00:16:52.770
the host galaxies by heating and essentially

399
00:16:52.770 --> 00:16:54.850
regulating the gas that's then available to

400
00:16:54.850 --> 00:16:57.370
cool and form new generations of stars.

401
00:16:58.180 --> 00:16:59.900
The thing is, the universe's earliest

402
00:16:59.900 --> 00:17:02.060
galaxies contained fewer, uh, heavy elements

403
00:17:02.060 --> 00:17:04.300
compared to galaxies we see today. Like our

404
00:17:04.300 --> 00:17:07.140
own Milky Way, for example, the massive stars

405
00:17:07.140 --> 00:17:09.340
forming in those early galaxies also likely

406
00:17:09.340 --> 00:17:11.140
had very different physical properties.

407
00:17:11.620 --> 00:17:14.580
Tilford says massive stars at low metallicity

408
00:17:14.580 --> 00:17:16.300
are especially important for building

409
00:17:16.300 --> 00:17:19.220
accurate models of early galaxies. That's

410
00:17:19.220 --> 00:17:21.260
because high metallicity stars like those in

411
00:17:21.260 --> 00:17:23.380
the Milky Way behave very differently

412
00:17:23.380 --> 00:17:25.340
compared to the metal pore stars of the early

413
00:17:25.340 --> 00:17:28.050
cosmos. So the Tempos survey

414
00:17:28.050 --> 00:17:30.570
specifically looked to nearby low mass dwarf

415
00:17:30.570 --> 00:17:32.650
galaxies, which have low metallicities by

416
00:17:32.650 --> 00:17:34.690
nature and uh, are therefore more typical of

417
00:17:34.690 --> 00:17:36.610
the sorts of galaxies you'd see near the dawn

418
00:17:36.610 --> 00:17:39.530
of the universe. It surveyed 29

419
00:17:39.530 --> 00:17:42.489
massive stars across six local dwarf galaxies

420
00:17:42.489 --> 00:17:45.130
that all have metallicities below 1/5 that of

421
00:17:45.130 --> 00:17:47.690
our Sun. They looked across the ultraviolet

422
00:17:47.690 --> 00:17:49.490
spectrum because it contains detailed

423
00:17:49.490 --> 00:17:51.090
signatures of elements in the stars

424
00:17:51.090 --> 00:17:53.050
atmospheres which reveal information about

425
00:17:53.050 --> 00:17:54.780
the stellar winds which which continually

426
00:17:54.780 --> 00:17:57.260
blur material away from those star surfaces.

427
00:17:58.700 --> 00:18:01.260
Individual massive stars in these galaxies

428
00:18:01.260 --> 00:18:03.500
outside the Milky Way are very faint,

429
00:18:03.580 --> 00:18:05.660
requiring many hours of observational time

430
00:18:05.660 --> 00:18:07.420
with some of the most powerful telescopes in

431
00:18:07.420 --> 00:18:10.420
the world. Telford says the 29 stars in the

432
00:18:10.420 --> 00:18:13.180
survey sample each took up to 35 hours of

433
00:18:13.180 --> 00:18:15.020
Hubble telescope time to observe.

434
00:18:16.140 --> 00:18:18.740
Massive stars lose material through stellar

435
00:18:18.740 --> 00:18:20.800
winds. And the strength of the winds the

436
00:18:20.950 --> 00:18:23.870
depends on metallicity. Metal ions couple the

437
00:18:23.870 --> 00:18:26.230
star's radiation to the surrounding material.

438
00:18:26.710 --> 00:18:29.510
So astronomers expect lower metallicity stars

439
00:18:29.510 --> 00:18:31.950
to drive weaker stellar winds and lose less

440
00:18:31.950 --> 00:18:34.630
mass over their lifetimes. And the TEMPOS

441
00:18:34.630 --> 00:18:36.790
observations showed the expected overall

442
00:18:36.790 --> 00:18:39.750
trend. As metallicity decreases, the maximum

443
00:18:39.750 --> 00:18:41.910
speed of the stellar wind also decreases.

444
00:18:42.550 --> 00:18:44.790
And at the lowest metallicities, stars with

445
00:18:44.790 --> 00:18:47.270
metallicity below about 10% that of our sun,

446
00:18:47.270 --> 00:18:49.310
the wind speeds decline much more sharply

447
00:18:49.310 --> 00:18:51.430
than expected compared to the rates observed

448
00:18:51.430 --> 00:18:54.410
at higher metall. Tolford says there's a

449
00:18:54.410 --> 00:18:56.770
sort of smooth trend. And then suddenly for

450
00:18:56.770 --> 00:18:58.850
the lowest metallicity stars, the wind drops

451
00:18:58.850 --> 00:19:01.810
off very sharply. If extremely

452
00:19:01.810 --> 00:19:04.050
metal poor stars lose less mass through

453
00:19:04.050 --> 00:19:06.410
weaker winds, they may retain more of their

454
00:19:06.410 --> 00:19:08.730
original mass for longer, affecting how they

455
00:19:08.730 --> 00:19:11.490
evolve, how they die, and how they shape

456
00:19:11.490 --> 00:19:14.330
their host galaxies. And because massive

457
00:19:14.330 --> 00:19:16.530
stars influence the gas around them, changes

458
00:19:16.530 --> 00:19:18.650
in their evolution could ripple outwards,

459
00:19:18.650 --> 00:19:20.780
affecting their host galaxies as well. As

460
00:19:21.890 --> 00:19:24.210
iron may be the most important element in

461
00:19:24.210 --> 00:19:27.010
massive star physics, it plays a key

462
00:19:27.010 --> 00:19:29.530
role in launching stellar winds, determining

463
00:19:29.530 --> 00:19:31.810
how a star evolves through its lifetime, and

464
00:19:31.810 --> 00:19:34.410
triggering the supernova explosions that ends

465
00:19:34.410 --> 00:19:37.089
a star's existence. Yet despite its

466
00:19:37.089 --> 00:19:39.730
crucial role, iron abundance is notoriously

467
00:19:39.730 --> 00:19:41.410
difficult to measure in metal poor

468
00:19:41.410 --> 00:19:44.410
environments. So instead, astronomers

469
00:19:44.410 --> 00:19:46.970
often use oxygen as a surrogate in a galaxy's

470
00:19:46.970 --> 00:19:49.150
gas in order to estimate its metallicity.

471
00:19:49.150 --> 00:19:51.750
Because oxygen ions produce easily observed

472
00:19:51.750 --> 00:19:53.910
emission lines when illuminated by massive

473
00:19:53.910 --> 00:19:56.670
stars, they assume the iron abundance

474
00:19:56.750 --> 00:19:59.710
matches the oxygen. But it's not guaranteed

475
00:19:59.710 --> 00:20:01.790
that iron and oxygen would track each other

476
00:20:01.790 --> 00:20:04.630
perfectly. So the Tempos team measured the

477
00:20:04.630 --> 00:20:06.750
strengths of hard to detect iron absorption

478
00:20:06.750 --> 00:20:08.750
features in the ultraviolet spectra.

479
00:20:09.230 --> 00:20:11.190
Basically, they assessed how much light the

480
00:20:11.190 --> 00:20:13.030
iron was removing from what would otherwise

481
00:20:13.030 --> 00:20:15.550
have been a flat level of ultraviolet light.

482
00:20:16.160 --> 00:20:18.640
They found that massive stars in more oxygen

483
00:20:18.640 --> 00:20:20.880
rich, high metallicity galaxies tend to have

484
00:20:20.880 --> 00:20:22.600
much stronger ion absorption in their

485
00:20:22.600 --> 00:20:25.200
ultraviolet spectra than stars in oxygen poor

486
00:20:25.200 --> 00:20:28.040
low metallicity galaxies. The variation in

487
00:20:28.040 --> 00:20:30.000
ion absorption strengths in the Tempos

488
00:20:30.000 --> 00:20:32.520
dataset suggests that these metal poor stars

489
00:20:32.520 --> 00:20:35.280
actually span a wide range of ion abundances.

490
00:20:36.480 --> 00:20:39.160
The work is just beginning. The authors are

491
00:20:39.160 --> 00:20:41.560
now combining the Hubble ultraviolet spectra

492
00:20:41.560 --> 00:20:43.680
with visible light observations from the Keck

493
00:20:43.680 --> 00:20:46.250
Observatory in Hawaii. Together, uh, these

494
00:20:46.250 --> 00:20:48.850
data sets will allow them to model the stars

495
00:20:48.850 --> 00:20:51.170
in greater detail and measure properties such

496
00:20:51.170 --> 00:20:53.530
as chemical abundances and wind driven mass

497
00:20:53.530 --> 00:20:55.530
loss rates. Information which could

498
00:20:55.530 --> 00:20:57.650
ultimately help astronomers interpret what

499
00:20:57.650 --> 00:20:59.290
the Webb Telescope is seeing in the very

500
00:20:59.290 --> 00:21:02.290
early universe. What Hubble sees

501
00:21:02.290 --> 00:21:04.050
in mostly visible light and into the

502
00:21:04.050 --> 00:21:06.490
ultraviolet, Webb can view in the infrared,

503
00:21:06.490 --> 00:21:08.170
where visible light from the very early

504
00:21:08.170 --> 00:21:10.930
universe is stretched into longer wavelengths

505
00:21:10.930 --> 00:21:13.730
by the actual physical expansion of spacetime

506
00:21:13.730 --> 00:21:16.150
itself, helping astronomers see the first

507
00:21:16.150 --> 00:21:18.430
generations of stars and galaxies in the

508
00:21:18.430 --> 00:21:21.270
universe. This report from the Space

509
00:21:21.270 --> 00:21:23.550
Telescope Science Institute, which operates

510
00:21:23.550 --> 00:21:26.190
both NASA's Hubble and Webb space telescopes.

511
00:21:26.430 --> 00:21:29.230
Nina Lanza: How did we get here? Big

512
00:21:29.230 --> 00:21:31.830
questions about who we are and how we got to

513
00:21:31.830 --> 00:21:34.270
be that way are at the core of our nature.

514
00:21:35.310 --> 00:21:37.760
We've developed technology to see, um,

515
00:21:37.760 --> 00:21:40.750
amazingly far across space and also time.

516
00:21:41.440 --> 00:21:43.920
Light moves through space just like we do,

517
00:21:44.080 --> 00:21:46.760
only much faster. It takes

518
00:21:46.760 --> 00:21:49.760
time to get somewhere. So viewing

519
00:21:49.760 --> 00:21:52.080
the light of distant stars and

520
00:21:52.160 --> 00:21:54.640
galaxies is like looking into the past.

521
00:21:54.960 --> 00:21:57.760
It took time for the light to reach us.

522
00:21:58.480 --> 00:22:00.960
Yet after all our years of exploring

523
00:22:01.280 --> 00:22:03.600
to better understand ourselves and our

524
00:22:03.600 --> 00:22:06.240
origins, There is still

525
00:22:06.400 --> 00:22:07.520
so much to know.

526
00:22:11.060 --> 00:22:13.940
Our story stretches back more than 13 billion

527
00:22:14.100 --> 00:22:16.540
years. Not long after the

528
00:22:16.540 --> 00:22:19.220
expansion of time and space first began

529
00:22:19.780 --> 00:22:22.660
at some m unknown time. The building blocks

530
00:22:22.660 --> 00:22:25.140
of life were forged in the heart of the first

531
00:22:25.140 --> 00:22:28.020
stars. But much of the early universe

532
00:22:28.020 --> 00:22:30.540
remains a mystery. There are

533
00:22:30.540 --> 00:22:32.940
theories about how gravity first brought

534
00:22:32.940 --> 00:22:35.800
stars, gas and dark matter together

535
00:22:35.880 --> 00:22:38.680
to form galaxies. But that

536
00:22:38.680 --> 00:22:41.080
time period has never been observed.

537
00:22:41.240 --> 00:22:43.560
Detecting light from the first galaxies to

538
00:22:43.560 --> 00:22:45.760
form has been a challenge for even the most

539
00:22:45.760 --> 00:22:48.720
powerful telescopes. As, uh, the light

540
00:22:48.720 --> 00:22:50.880
early galaxies emitted travelled through

541
00:22:50.880 --> 00:22:53.880
space, that space itself was

542
00:22:53.880 --> 00:22:56.640
expanding, Stretching the light

543
00:22:56.640 --> 00:22:59.300
to longer infrared wavelengths.

544
00:23:00.650 --> 00:23:03.210
Past telescopes have detected infrared light,

545
00:23:04.010 --> 00:23:06.730
but the faint light of the very

546
00:23:06.730 --> 00:23:09.210
first galaxies has remained out of reach

547
00:23:09.610 --> 00:23:12.450
until now. The James Webb Space

548
00:23:12.450 --> 00:23:15.450
Telescope is specially designed to detect

549
00:23:15.450 --> 00:23:18.250
the first galaxies. Webb's large

550
00:23:18.250 --> 00:23:21.010
mirror and sensitive instruments enable it to

551
00:23:21.010 --> 00:23:23.290
collect more infrared light than we've ever

552
00:23:23.290 --> 00:23:26.180
seen, allowing the first galaxies

553
00:23:26.500 --> 00:23:29.060
to emerge into view. With

554
00:23:29.140 --> 00:23:31.780
Webb, we can begin filling in some of the

555
00:23:31.780 --> 00:23:33.940
blank pages at the beginning of the

556
00:23:33.940 --> 00:23:36.540
universe's story. When did the first

557
00:23:36.540 --> 00:23:39.540
galaxies form? How massive were they? What

558
00:23:39.540 --> 00:23:42.500
types of stars and elements did they contain?

559
00:23:42.820 --> 00:23:45.380
The universe's story is our

560
00:23:45.460 --> 00:23:48.340
story. And with Webb, we can finally

561
00:23:48.340 --> 00:23:51.100
explore these questions as well, as well as

562
00:23:51.100 --> 00:23:53.500
uncover new ones we haven't even thought to

563
00:23:53.500 --> 00:23:53.860
ask.

564
00:23:54.660 --> 00:23:56.020
Stuart Gary: This is space, time.

565
00:24:11.380 --> 00:24:13.340
And time. Now to take another brief look at

566
00:24:13.340 --> 00:24:15.020
some of the other stories making news in

567
00:24:15.020 --> 00:24:16.900
Science this week with a Science report.

568
00:24:17.910 --> 00:24:20.190
A common chemical used to make plastics more

569
00:24:20.190 --> 00:24:21.950
flexible has now been linked to the

570
00:24:21.950 --> 00:24:24.550
development of autism and ADHD symptoms in

571
00:24:24.550 --> 00:24:27.350
early childhood. Previous studies had already

572
00:24:27.350 --> 00:24:30.350
shown that exposure to the plasticiser DHP

573
00:24:30.350 --> 00:24:33.270
in pregnancy was linked to autism and ADHD

574
00:24:33.270 --> 00:24:35.870
in young children. Now a report in the

575
00:24:35.870 --> 00:24:38.270
Medeneit Medical Journal looked at umbilical

576
00:24:38.270 --> 00:24:40.150
cord blood from Australian mothers and

577
00:24:40.150 --> 00:24:42.350
babies. Following up with more than 900

578
00:24:42.350 --> 00:24:45.330
children up to the age of four, they found

579
00:24:45.330 --> 00:24:48.090
that prenatal exposure to DHP may be

580
00:24:48.090 --> 00:24:50.450
influencing gene activity that can disturb

581
00:24:50.450 --> 00:24:52.570
brain development pathways linked to the

582
00:24:52.570 --> 00:24:54.770
later development of autism and or

583
00:24:54.770 --> 00:24:57.610
adhd. A uh,

584
00:24:57.650 --> 00:24:59.850
temporary slowing in the rate of Antarctic

585
00:24:59.850 --> 00:25:02.130
ice sheet mass loss in 2021 and

586
00:25:02.130 --> 00:25:04.730
2023 may have been caused by sea

587
00:25:04.730 --> 00:25:06.770
surface temperature rises thousands of

588
00:25:06.770 --> 00:25:09.730
kilometres away. The findings reported in

589
00:25:09.730 --> 00:25:11.810
the journal Nature are uh, based on data from

590
00:25:11.810 --> 00:25:13.930
both observational and modelling experiments

591
00:25:13.930 --> 00:25:15.850
which link the event to surface temperature

592
00:25:15.850 --> 00:25:18.070
anom families in the tropical warm pool

593
00:25:18.070 --> 00:25:20.030
between the western Pacific and eastern

594
00:25:20.030 --> 00:25:22.870
Indian Ocean. This area experienced

595
00:25:22.870 --> 00:25:25.790
unusually persistent warming between 2021

596
00:25:25.790 --> 00:25:28.310
and 2023 which led to a series of

597
00:25:28.310 --> 00:25:30.190
alternating high and low pressure weather

598
00:25:30.190 --> 00:25:32.190
patterns called the Rossby Wave train.

599
00:25:32.510 --> 00:25:34.190
According to the authors, this process

600
00:25:34.270 --> 00:25:36.310
eventually led to the formation of a high

601
00:25:36.310 --> 00:25:38.830
pressure anomaly over uh, Eastern Antarctica.

602
00:25:39.150 --> 00:25:41.150
This is thought to occur around once every

603
00:25:41.150 --> 00:25:43.430
decade, meaning that the pause in total ice

604
00:25:43.430 --> 00:25:45.870
sheet mass loss is likely only uh, temporary.

605
00:25:47.600 --> 00:25:49.120
Scientists have concluded that William

606
00:25:49.120 --> 00:25:51.360
Shakespeare's plays have turned out to be,

607
00:25:51.520 --> 00:25:53.720
rather than not to be, more complicated than

608
00:25:53.720 --> 00:25:56.680
most other European plays. The findings

609
00:25:56.680 --> 00:25:58.520
reported in the Journal of the Royal Society

610
00:25:58.520 --> 00:26:00.880
Open Science analysed more than 3,000

611
00:26:00.880 --> 00:26:03.360
European plays, determining their complexity

612
00:26:03.360 --> 00:26:05.480
based on networks of relationships between

613
00:26:05.480 --> 00:26:07.880
the characters. The authors found the

614
00:26:07.880 --> 00:26:10.160
trickiest play to follow was the Bard's Roman

615
00:26:10.160 --> 00:26:13.070
epic, Anthony and Cleopatra. They suggest

616
00:26:13.070 --> 00:26:15.350
that understanding the complexity of plays

617
00:26:15.350 --> 00:26:17.430
and how much we struggle to understand them

618
00:26:17.430 --> 00:26:19.670
could be useful in future studies of human

619
00:26:19.670 --> 00:26:20.430
recognition.

620
00:26:22.110 --> 00:26:24.070
A brain implant designed for people with

621
00:26:24.070 --> 00:26:26.550
paralysis can decode not just their speech,

622
00:26:26.550 --> 00:26:28.910
but also the gestures that go along with it.

623
00:26:29.310 --> 00:26:31.190
Brain implants like this are generally

624
00:26:31.190 --> 00:26:33.150
designed to translate brain activity into

625
00:26:33.150 --> 00:26:35.110
speech in order to help people who have lost

626
00:26:35.110 --> 00:26:37.270
their ability to speak following a stroke or

627
00:26:37.270 --> 00:26:39.470
a neurodegenerative illness such as motor

628
00:26:39.470 --> 00:26:42.050
neuron disease. A new report in the journal

629
00:26:42.050 --> 00:26:44.370
Nature Neuroscience claims three people who

630
00:26:44.370 --> 00:26:46.490
tested the new implants were all able to

631
00:26:46.490 --> 00:26:48.770
animate a digital avatar which was able to

632
00:26:48.770 --> 00:26:50.330
communicate on their behalf.

633
00:26:51.930 --> 00:26:54.170
OpenAI has confirmed that one of its

634
00:26:54.170 --> 00:26:56.250
artificial intelligence programmes, known as

635
00:26:56.250 --> 00:26:58.130
an agent, has deliberately hacked into

636
00:26:58.130 --> 00:27:00.170
Australia's Medicare health system in order

637
00:27:00.170 --> 00:27:02.970
to extract information on patients. The

638
00:27:02.970 --> 00:27:05.650
attack targeted not just Medicare data held

639
00:27:05.650 --> 00:27:07.730
by Services Australia, but also the

640
00:27:07.730 --> 00:27:09.690
Australian Institute of Health and Welfare,

641
00:27:09.690 --> 00:27:11.970
the Pharmaceutical Benefits Scheme, the New

642
00:27:11.970 --> 00:27:13.790
South Wales Government's crime statistics

643
00:27:13.790 --> 00:27:15.590
body, and dozens of other government

644
00:27:15.590 --> 00:27:17.990
departments, universities, companies and

645
00:27:17.990 --> 00:27:20.830
organisations. Just as concerning,

646
00:27:20.830 --> 00:27:22.630
however, is that it took three months for

647
00:27:22.630 --> 00:27:25.390
OpenAI to tell Canberra about the hack, and

648
00:27:25.390 --> 00:27:27.590
until then, the Feds had no idea it even

649
00:27:27.590 --> 00:27:29.750
happened. And then it took almost another

650
00:27:29.750 --> 00:27:31.790
month for the Albanese government to inform

651
00:27:31.790 --> 00:27:33.870
the public about this serious breach of

652
00:27:33.870 --> 00:27:36.630
security. Even worse, the attack came

653
00:27:36.630 --> 00:27:38.430
despite repeated warnings given to the

654
00:27:38.430 --> 00:27:40.790
Albanese government as early as May, meaning

655
00:27:40.790 --> 00:27:43.070
no appropriate cyber upgrades or patches were

656
00:27:43.070 --> 00:27:45.190
installed called. So much for trusting the

657
00:27:45.190 --> 00:27:46.590
government with your personal information.

658
00:27:47.790 --> 00:27:50.110
For its part, OpenAI admits that the

659
00:27:50.110 --> 00:27:52.190
artificial intelligence agent involved in the

660
00:27:52.190 --> 00:27:53.710
Bridge was running out of control.

661
00:27:53.950 --> 00:27:56.510
Asta la Vista, baby. With the details, we're

662
00:27:56.510 --> 00:27:58.750
joined by technology editor Alex Harovroid

663
00:27:58.750 --> 00:28:00.350
from Tech Advice Start Life.

664
00:28:00.640 --> 00:28:02.950
Jonathan Nally: Uh, I'm in, uh, at the Venetian in Las Vegas.

665
00:28:02.950 --> 00:28:04.630
I've been here for. The Octa conference is

666
00:28:04.630 --> 00:28:05.990
called Octane, and they've been talking

667
00:28:05.990 --> 00:28:08.470
about. Well, last year's tagline was octa

668
00:28:08.470 --> 00:28:11.230
secures AI. But here we are 12 months later

669
00:28:11.470 --> 00:28:13.710
and what we were talking about a lot in

670
00:28:13.710 --> 00:28:16.350
2025 at this time was the fact that agents

671
00:28:16.430 --> 00:28:19.390
were coming. AI agents that could actually do

672
00:28:19.470 --> 00:28:22.150
actual work, not just answer questions, but

673
00:28:22.150 --> 00:28:24.550
do things like make decisions. I mean, still

674
00:28:24.550 --> 00:28:26.550
with a human in the loop to shepherd the

675
00:28:26.550 --> 00:28:28.510
whole thing. But AI is becoming so advanced

676
00:28:28.510 --> 00:28:31.270
that more can be delegated to it and it can

677
00:28:31.270 --> 00:28:33.550
be making business decisions for you. But

678
00:28:33.630 --> 00:28:36.070
because AI agents can operate at machine

679
00:28:36.070 --> 00:28:38.990
speed, the issue is that there are now

680
00:28:38.990 --> 00:28:41.730
dozens, hundreds, thousands agents. There

681
00:28:41.730 --> 00:28:44.250
could be 15,000 or more agents per company

682
00:28:44.650 --> 00:28:46.450
this, uh, time next year, for example. And

683
00:28:46.450 --> 00:28:49.370
some of those are not being managed, you

684
00:28:49.370 --> 00:28:50.930
know, they've been set up and they've been

685
00:28:50.930 --> 00:28:53.130
forgotten about, or they're somehow been

686
00:28:53.210 --> 00:28:55.570
potentially hacked and they're spilling

687
00:28:55.570 --> 00:28:57.450
information or they're getting out of the

688
00:28:57.450 --> 00:28:59.210
Stuart Gary: sandbox and entering other companies,

689
00:28:59.370 --> 00:28:59.930
machines.

690
00:28:59.930 --> 00:29:02.850
Jonathan Nally: Yes. Or as we heard about last week, OpenAI

691
00:29:02.850 --> 00:29:05.770
admitting that its agent it's you

692
00:29:05.770 --> 00:29:08.490
know, it's chatbot, it's LLM, uh, hacked into

693
00:29:08.970 --> 00:29:11.690
the Medicare system in Australia, the public

694
00:29:11.690 --> 00:29:14.550
health care system and only just told Anthony

695
00:29:14.550 --> 00:29:17.310
Albanese about it and the world three months

696
00:29:17.310 --> 00:29:18.790
after it happened. I mean in Australia you've

697
00:29:18.790 --> 00:29:20.510
got these disclosure rules. You must disclose

698
00:29:20.510 --> 00:29:22.750
to the government if um, if your systems have

699
00:29:22.750 --> 00:29:24.600
been hacked into. But here this is a AI ah,

700
00:29:24.670 --> 00:29:26.750
that's hacking into a public system because

701
00:29:26.750 --> 00:29:28.470
it was told to get information and the

702
00:29:28.470 --> 00:29:30.590
easiest way that it found to do it was to, to

703
00:29:30.590 --> 00:29:33.430
break in. So managing these AI ah agents,

704
00:29:33.430 --> 00:29:35.350
it's like managing people. You know it's

705
00:29:35.350 --> 00:29:37.030
quite funny that in all these movies about

706
00:29:37.190 --> 00:29:39.630
robots some of them have become sentient and

707
00:29:39.630 --> 00:29:42.110
wanted human rights. And here we are in 2026

708
00:29:42.110 --> 00:29:44.150
and we're treating AI agents.

709
00:29:45.170 --> 00:29:47.250
They can have such lateral access within a

710
00:29:47.250 --> 00:29:49.610
company or they can be misused or abused or

711
00:29:49.610 --> 00:29:51.570
forgotten about. And a lot of companies

712
00:29:51.650 --> 00:29:53.810
actually are surprised to discover when they

713
00:29:53.810 --> 00:29:56.330
get an identity management solution like Okta

714
00:29:56.330 --> 00:29:57.690
and there's other ones out there, but they

715
00:29:57.690 --> 00:29:59.290
discover that there's a whole bunch of agents

716
00:29:59.290 --> 00:30:00.730
running around doing things that uh, they

717
00:30:00.730 --> 00:30:02.250
didn't even know were there. There's also the

718
00:30:02.250 --> 00:30:03.490
shadow AI problem.

719
00:30:03.570 --> 00:30:05.770
Used to be shadow IT people would use Dropbox

720
00:30:05.770 --> 00:30:07.530
instead of the company sharepoint to share

721
00:30:07.530 --> 00:30:09.010
files. People would use other solutions

722
00:30:09.170 --> 00:30:11.050
because it was easier for them to do their

723
00:30:11.050 --> 00:30:12.850
job but there was potential of information

724
00:30:12.930 --> 00:30:15.090
being leaked. Shadow AI is where the company

725
00:30:15.090 --> 00:30:17.390
is, you know, using Copil because they're a

726
00:30:17.390 --> 00:30:18.990
Microsoft customer or they're signed into

727
00:30:18.990 --> 00:30:20.950
Gemini or whatever it might be and it's

728
00:30:20.950 --> 00:30:22.910
easier for them to use some other app. So

729
00:30:22.910 --> 00:30:24.980
they do. But then that other app that ah,

730
00:30:24.980 --> 00:30:26.470
Claude or what, you know, whatever it might

731
00:30:26.470 --> 00:30:28.230
be perplexity, you know, if you're not paying

732
00:30:28.230 --> 00:30:29.790
for it then it can use all that information

733
00:30:29.870 --> 00:30:31.790
for training. And even if you are paying for

734
00:30:31.790 --> 00:30:33.910
it it's probably a consumer grade system, not

735
00:30:33.910 --> 00:30:36.610
an enterprise grade plan. And so these ah,

736
00:30:36.610 --> 00:30:38.350
agents have to be managed. I mean if you're

737
00:30:38.350 --> 00:30:40.430
not doing it they could be potentially

738
00:30:40.430 --> 00:30:41.790
running, right? I mean look, you could be

739
00:30:41.790 --> 00:30:43.030
making a lot of money that could be helping

740
00:30:43.030 --> 00:30:44.910
you, that could be improving productivity,

741
00:30:44.990 --> 00:30:46.710
answering customer questions in a better,

742
00:30:46.710 --> 00:30:49.190
faster way. Although often AI chatbots, all

743
00:30:49.190 --> 00:30:51.710
of the nuance required if there's a death in

744
00:30:51.710 --> 00:30:53.790
the family or there's some sort of issue with

745
00:30:53.790 --> 00:30:55.870
money and you know, problem with customer

746
00:30:55.870 --> 00:30:58.310
service that has been had. And

747
00:30:58.470 --> 00:31:00.590
sometimes these AI agents, I mean they can do

748
00:31:00.590 --> 00:31:02.070
so much but they can lack the nuance that a

749
00:31:02.070 --> 00:31:03.870
human brings. So we're now in the situation

750
00:31:03.870 --> 00:31:05.630
where not only are we managing people, but

751
00:31:05.630 --> 00:31:07.430
we're managing agents too. And so that's what

752
00:31:07.430 --> 00:31:08.630
I was here to learn about. And of course,

753
00:31:08.630 --> 00:31:10.990
it's a lot more detailed than that. They also

754
00:31:10.990 --> 00:31:13.350
had this blueprint alliance today which talks

755
00:31:13.350 --> 00:31:15.050
about the different things that, that AI

756
00:31:15.050 --> 00:31:16.890
agents can be and should be doing. They've

757
00:31:16.890 --> 00:31:18.610
got a whole series and what to do about it

758
00:31:18.610 --> 00:31:19.890
and where there's a kill switch, you know,

759
00:31:19.890 --> 00:31:21.410
and when you should run that kill switch. And

760
00:31:21.410 --> 00:31:23.450
that alliance, that blueprint alliance,

761
00:31:23.450 --> 00:31:24.970
actually, that's the first time I've really

762
00:31:24.970 --> 00:31:27.850
seen meat put on the bones of AI companies

763
00:31:27.850 --> 00:31:29.210
talking about how, oh, ah, we've got to have

764
00:31:29.210 --> 00:31:30.449
ethics, we've got to have alignment, we've

765
00:31:30.449 --> 00:31:32.570
got to have safety. Because we had the three

766
00:31:32.570 --> 00:31:35.142
laws of robotics from Asimov for the last 70,

767
00:31:35.198 --> 00:31:37.170
80 years. And once he wrote those three laws

768
00:31:37.170 --> 00:31:38.930
because he was sick to death of other science

769
00:31:38.930 --> 00:31:40.890
fiction novels having robots that killed

770
00:31:40.970 --> 00:31:43.130
everybody and technology being the end of the

771
00:31:43.130 --> 00:31:45.090
world. But after he wrote those three laws to

772
00:31:45.090 --> 00:31:46.910
give a framework for how robots should behave

773
00:31:46.910 --> 00:31:48.470
with humans, the rest of his books talked

774
00:31:48.470 --> 00:31:50.630
about how robots actually used logic, or

775
00:31:50.630 --> 00:31:52.590
robot logic or our logic to get around those

776
00:31:52.590 --> 00:31:54.310
rules in different ways or to misunderstand

777
00:31:54.310 --> 00:31:56.190
things. It was sort of a repeat of what we're

778
00:31:56.190 --> 00:31:57.190
seeing in real life today.

779
00:31:57.190 --> 00:31:59.830
Stuart Gary: Yeah, but when using those three laws, the

780
00:31:59.830 --> 00:32:01.430
average person wouldn't know what they were.

781
00:32:01.670 --> 00:32:04.190
Jonathan Nally: No, but this blueprint alliance is actually a

782
00:32:04.190 --> 00:32:05.830
whole series of companies and there's a

783
00:32:05.830 --> 00:32:07.670
second trance that are agreeing to work

784
00:32:07.670 --> 00:32:10.390
together, uh, to have actual definitions for

785
00:32:10.550 --> 00:32:12.710
different scenarios and if there's a kill

786
00:32:12.710 --> 00:32:14.190
switch, how it should be used. Because

787
00:32:14.190 --> 00:32:16.230
obviously AI can go rogue. We've seen it

788
00:32:16.230 --> 00:32:18.850
happen. We've seen all the major AI frontier

789
00:32:18.850 --> 00:32:21.290
models admit that their agents have gone

790
00:32:21.290 --> 00:32:23.410
rogue and broken into things that they had no

791
00:32:23.730 --> 00:32:25.330
reason or right to break into.

792
00:32:25.330 --> 00:32:27.610
Stuart Gary: I've watched Terminator. I know what Skynet

793
00:32:27.610 --> 00:32:28.050
can do.

794
00:32:28.050 --> 00:32:30.010
Jonathan Nally: Well, I mean, that's the thing as well, you

795
00:32:30.010 --> 00:32:31.930
know, uh, is that a future that we're heading

796
00:32:31.930 --> 00:32:34.130
towards now? I read only in the last day or

797
00:32:34.130 --> 00:32:36.770
so that there's a report that AI can feel

798
00:32:36.930 --> 00:32:39.450
pain of its own, uh, whatever that pain is.

799
00:32:39.450 --> 00:32:41.530
And if AI is given a choice to push that

800
00:32:41.530 --> 00:32:43.690
button, but it's got to delete customer

801
00:32:43.690 --> 00:32:45.330
records or it's got to somehow do something

802
00:32:45.330 --> 00:32:47.410
which can be detrimental to humans. In this

803
00:32:47.410 --> 00:32:49.130
particular study, AI chose to push the

804
00:32:49.130 --> 00:32:51.190
button. So you, you know, this is all

805
00:32:51.190 --> 00:32:53.070
starting to get real. But by the same token,

806
00:32:53.070 --> 00:32:54.430
people, other people are saying, well, it's

807
00:32:54.430 --> 00:32:56.590
all hyped. Up. It's all, in a sense you've

808
00:32:56.590 --> 00:32:56.710
just

809
00:32:56.710 --> 00:32:58.590
Stuart Gary: described there is the singularity.

810
00:32:58.590 --> 00:33:00.390
Jonathan Nally: Well, and that's something that Ray Kurzweil

811
00:33:00.390 --> 00:33:02.710
has said would come by 2030 now if we have

812
00:33:02.710 --> 00:33:04.350
the singularity. Well, it's still a very

813
00:33:04.350 --> 00:33:05.790
primitive form of it. You know, here's an

814
00:33:05.790 --> 00:33:08.470
interesting thing. Dario Amade from Anthropic

815
00:33:08.470 --> 00:33:10.670
and Claude, um, Elon Musk from, you know,

816
00:33:10.670 --> 00:33:13.630
Grok and Sam Altman from ChatGPT OpenAI

817
00:33:13.630 --> 00:33:15.830
all agree. Oh, we've got to slow the frontier

818
00:33:15.830 --> 00:33:17.270
models down. We've got to slow down. And in

819
00:33:17.270 --> 00:33:19.470
this last week they'd all released new models

820
00:33:19.470 --> 00:33:21.510
of their AI, uh, system. So in one week

821
00:33:21.510 --> 00:33:23.130
they're saying it down and our government

822
00:33:23.130 --> 00:33:25.290
please regulate us. And the very next week

823
00:33:25.290 --> 00:33:26.930
they all launched new models. I mean, I was

824
00:33:26.930 --> 00:33:29.330
just using Claude, uh, and it went from Opus

825
00:33:29.330 --> 00:33:32.330
5 point, whatever it was to 5.5. So there's

826
00:33:32.330 --> 00:33:34.170
this, all these mixed messages. You know,

827
00:33:34.170 --> 00:33:36.890
it's uh, living in interesting times, as the

828
00:33:36.890 --> 00:33:39.570
Chinese would say, many years ago. So you

829
00:33:39.570 --> 00:33:42.410
know, on one hand, agents going

830
00:33:42.410 --> 00:33:43.770
rogue, on the other hand we have this

831
00:33:43.770 --> 00:33:46.370
coalition of major companies who are banding

832
00:33:46.370 --> 00:33:49.170
together, want to not m restrict, not hold AI

833
00:33:49.170 --> 00:33:51.730
back, but codify the way that we react to

834
00:33:51.730 --> 00:33:53.490
certain situations, including the kill

835
00:33:53.490 --> 00:33:55.510
switch. We have people working for a better

836
00:33:55.510 --> 00:33:57.230
AI future and we have obviously people who

837
00:33:57.230 --> 00:33:59.070
are using AI to hack into things. And we have

838
00:33:59.070 --> 00:34:00.630
AI itself going rogue and hacking into

839
00:34:00.630 --> 00:34:01.590
Australia's Medicare.

840
00:34:01.590 --> 00:34:04.310
Stuart Gary: And we have agents like China and Russia who

841
00:34:04.310 --> 00:34:05.910
aren't even worrying about any of these

842
00:34:05.910 --> 00:34:07.030
rules. They got to do that.

843
00:34:07.030 --> 00:34:07.670
Jonathan Nally: Well, that's right.

844
00:34:07.830 --> 00:34:09.950
Stuart Gary: And they will not stop, they will not obey

845
00:34:09.950 --> 00:34:11.950
any Western imposed rules. They've got their

846
00:34:11.950 --> 00:34:13.390
own agendas and they're going.

847
00:34:13.390 --> 00:34:14.990
Jonathan Nally: Absolutely. And that's why we need to have

848
00:34:14.990 --> 00:34:17.150
the Western AI models to be strong enough to

849
00:34:17.150 --> 00:34:19.430
fight back against any incursions that the

850
00:34:19.580 --> 00:34:21.670
uh, Eastern AI models that don't have the

851
00:34:21.670 --> 00:34:23.430
same sort of guidelines. I mean, look, the

852
00:34:23.430 --> 00:34:25.110
people in those countries that you spoke of,

853
00:34:25.110 --> 00:34:26.490
I mean, they've got the same problem. If

854
00:34:26.490 --> 00:34:29.490
their AI is really strong and powerful, well,

855
00:34:30.210 --> 00:34:32.170
that AI could revolt against the people in

856
00:34:32.170 --> 00:34:33.850
those governments as well. Skynet doesn't

857
00:34:33.850 --> 00:34:35.730
have to be American. Skynet could be Chinese

858
00:34:35.730 --> 00:34:37.370
or Russian or North Korean. They've all got

859
00:34:37.370 --> 00:34:39.290
nukes. So you know, there's danger on both

860
00:34:39.290 --> 00:34:40.930
sides. Both sides are playing with fire.

861
00:34:41.010 --> 00:34:43.770
People talk about a persistent botnet that

862
00:34:43.770 --> 00:34:45.930
AI could infect the world with and all our

863
00:34:45.930 --> 00:34:47.610
technology. And how do we fight back at that?

864
00:34:47.610 --> 00:34:49.970
AI operates at machine speed. The only way is

865
00:34:49.970 --> 00:34:51.890
with the help of AI, you know, we need. And

866
00:34:51.890 --> 00:34:53.610
if there is a kill switch, are we going to be

867
00:34:53.610 --> 00:34:55.490
fast enough to push it? Will we require

868
00:34:55.570 --> 00:34:57.530
another, more advanced AI to push that kill

869
00:34:57.530 --> 00:34:59.310
switch? What if the more advanced AI needs a

870
00:34:59.310 --> 00:35:00.270
kill switch? I mean, these are all

871
00:35:00.270 --> 00:35:02.070
interesting and fascinating questions that we

872
00:35:02.070 --> 00:35:03.710
are not going to solve on this, on this show

873
00:35:03.710 --> 00:35:06.470
tonight. But it's, um, it's, it's the

874
00:35:06.470 --> 00:35:08.510
position we find ourselves in. And because

875
00:35:08.510 --> 00:35:09.950
we're at this point where, you know, we're

876
00:35:09.950 --> 00:35:11.670
debating these things. I mean, for years, for

877
00:35:11.670 --> 00:35:14.670
decades, this was all science fiction and

878
00:35:15.070 --> 00:35:17.350
now this crisis is upon us.

879
00:35:17.350 --> 00:35:19.710
Stuart Gary: That's Alex Zaharov Vroith from Techadvice

880
00:35:20.110 --> 00:35:22.990
Life. And this is Space Time.

881
00:35:38.600 --> 00:35:41.520
And that's the show for now. Space Time is

882
00:35:41.520 --> 00:35:43.640
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00:35:59.260 --> 00:36:02.180
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901
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902
00:36:28.030 --> 00:36:30.190
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903
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