  Magnetic sounding using data collected from the Juno mission can be used to
provide constraints on Jupiter's interior. However, inwards continuation of
reconstructions assuming zero electrical conductivity and a representation in
spherical harmonics are limited by the enhancement of noise at small scales.
Here we describe new reconstructions of Jupiter's internal magnetic field based
on physics-informed neural networks and either the first 33 (PINN33) or the
first 50 (PINN50) of Juno's orbits. The method can resolve local structures,
and allows for weak ambient electrical currents. Our models are not hampered by
noise amplification at depth, and offer a much clearer picture of the interior
structure. We estimate that the dynamo boundary is at a fractional radius of
0.8. At this depth, the magnetic field is arranged into longitudinal bands, and
strong local features such as the great blue spot appear to be rooted in
neighbouring structures of oppositely signed flux.
