The Fort Worth Press - Robots pour cocktails and run marathons, but still can't multitask

USD -
AED 3.672962
AFN 65.000396
ALL 79.569641
AMD 363.410009
ANG 1.790365
AOA 918.000118
ARS 1512.732505
AUD 1.403509
AWG 1.8
AZN 1.684438
BAM 1.695609
BBD 2.01466
BDT 123.160418
BGN 1.683441
BHD 0.377012
BIF 2995
BMD 1
BND 1.273738
BOB 10.998357
BRL 5.144046
BSD 1.000308
BTN 95.98391
BWP 13.567066
BYN 3.037656
BYR 19600
BZD 2.011747
CAD 1.39515
CDF 2309.999597
CHF 0.819885
CLF 0.024143
CLP 953.330119
CNY 6.706399
CNH 6.706796
COP 3133.79
CRC 447.438348
CUC 1
CUP 26.5
CVE 95.999895
CZK 21.106303
DJF 177.71991
DKK 6.489345
DOP 58.850154
DZD 133.63037
EGP 52.199498
ERN 15
ETB 160.949926
EUR 0.86806
FJD 2.21295
FKP 0.741937
GBP 0.744595
GEL 2.603264
GGP 0.741937
GHS 11.505024
GIP 0.741937
GMD 73.99969
GNF 8795.314945
GTQ 7.636255
GYD 209.277425
HKD 7.844805
HNL 26.847168
HRK 6.531703
HTG 130.738787
HUF 316.004029
IDR 17690
ILS 3.027501
IMP 0.741937
INR 95.90965
IQD 1310.5
IRR 1374600.000237
ISK 121.320336
JEP 0.741937
JMD 157.856864
JOD 0.708988
JPY 155.228505
KES 129.498728
KGS 87.449898
KHR 4050.422208
KMF 427.000462
KPW 900.000318
KRW 1367.705023
KWD 0.30856
KYD 0.833583
KZT 444.773881
LAK 22392.336201
LBP 89575.662472
LKR 331.544497
LRD 173.548166
LSL 16.285389
LTL 2.95274
LVL 0.60489
LYD 6.345021
MAD 9.466964
MDL 17.439779
MGA 4325.19127
MKD 53.344315
MMK 2099.62457
MNT 3595.075141
MOP 8.082447
MRU 40.060447
MUR 47.290412
MVR 15.410502
MWK 1736.502094
MXN 17.15007
MYR 4.068397
MZN 63.892219
NAD 16.285247
NGN 1326.720329
NIO 36.811146
NOK 9.361295
NPR 153.579928
NZD 1.739085
OMR 0.384497
PAB 1.000282
PEN 3.355918
PGK 4.522953
PHP 62.724028
PKR 277.25311
PLN 3.781535
PYG 5918.765443
QAR 3.636395
RON 4.568901
RSD 101.865037
RUB 84.244494
RWF 1475.913668
SAR 3.753075
SBD 8.03625
SCR 14.650196
SDG 601.50092
SEK 9.78923
SGD 1.274225
SHP 0.742225
SLE 24.640299
SLL 20969.491881
SOS 571.673797
SRD 37.752497
STD 20697.981008
STN 21.240534
SVC 8.752834
SYP 13002.000254
SZL 16.283395
THB 33.282013
TJS 9.226022
TMT 3.5
TND 2.928519
TOP 2.40776
TRY 48.657898
TTD 6.782056
TWD 31.792499
TZS 2645.002985
UAH 44.609389
UGX 3916.077853
UYU 40.244484
UZS 11793.315705
VES 841.183975
VND 25998.5
VUV 118.157011
WST 2.736734
XAF 569.409897
XAG 0.01559
XAU 0.000231
XCD 2.70255
XCG 1.802758
XDR 0.707052
XOF 569.409897
XPF 103.393717
YER 236.499459
ZAR 16.289965
ZMK 9001.251421
ZMW 19.630588
ZWL 321.999592
SSP 5655.283496
MXV 1.944584
  • RYCEF

    0.2600

    19.3

    +1.35%

  • CMSC

    0.0990

    20.419

    +0.48%

  • RBGPF

    0.0000

    69.99

    0%

  • RIO

    -2.1950

    95.065

    -2.31%

  • RELX

    -0.0500

    34.17

    -0.15%

  • NGG

    0.9500

    75.88

    +1.25%

  • GSK

    0.1600

    50.17

    +0.32%

  • VOD

    -0.3850

    17.295

    -2.23%

  • CMSD

    0.1950

    20.265

    +0.96%

  • BCE

    -0.4300

    22.47

    -1.91%

  • BTI

    -0.4600

    56.06

    -0.82%

  • AZN

    0.3450

    162.195

    +0.21%

  • JRI

    -0.0100

    11.61

    -0.09%

  • BP

    -1.6700

    45.29

    -3.69%

  • BCC

    -1.2050

    74.725

    -1.61%

Robots pour cocktails and run marathons, but still can't multitask
Robots pour cocktails and run marathons, but still can't multitask / Photo: © AFP

Robots pour cocktails and run marathons, but still can't multitask

They can mix cocktails, run marathons and fold laundry. But humanoid robots are still a long way from doing lots of different jobs on command, whatever the marketing says.

Text size:

The gap was easy to spot at the Robotics Summit in Boston in late May. The glossy brochures promised one thing. The people who actually build the machines said another.

Elon Musk loves to show off his Optimus prototype, recently filmed jogging in short strides. Figure 03, a third-generation robot developed by Figure AI, can tidy and clean a living room by itself.

China's AgiBot and Matrix Robotics say their robots can greet visitors, serve coffee and give them a tour, a little like C-3PO from "Star Wars."

The reality is more modest.

"Most of the humanoids you see are being teleoperated, or they've got very specific paths and chores that they do," said Chris Matthieu of startup RealSense, which makes cameras for robots.

In other words, many are either run by a human with a remote control or stuck doing one narrow task.

Take Neo, the robot that 1X launched with great fanfare last October. It was billed as "the world's first consumer-ready humanoid robot designed to transform life at home" -- but was actually steered by a person off to the side.

Progress is real, though, and artificial intelligence is driving it. "I think AI has extremely accelerated that growth," said William Okazaki of sensor maker Renesas.

One big hurdle is the hands. Long the holy grail of robotics, they are getting close: robots can now grip with a delicate touch, and some sensors can even tell when they are touching human skin.

Much of this comes from a new kind of AI known as a VLA model, short for vision-language-action. It blends written instructions with what a camera sees in real time, so the robot can link what it is looking at to what it should do.

There is also the "world model" -- an AI that learns from vast amounts of images and video until it can predict what will happen next in the real world, such as how an object will shift when it is squeezed.

-- Hunt for data --

But an android that can do a bit of everything is still years off.

"For general purpose robots, it will take longer," said Daniel Fan of Innodisk, which makes parts for robots.

Plenty of humanoids are already out in the world -- Boston Dynamics' Atlas at Hyundai, Hexagon Robotics' AEON at a BMW site -- but these are trials, not final products.

"Until you actually get the robot actually trying to do the thing you think it can do, you don't really know," said Charlie Kemp of Hello Robot, which sells robots for people with limited mobility.

Running fully on their own, at scale, is not yet possible, "because there is not enough data," said Xinrui Bi of AgiBot.

To gather it, companies are setting up cameras everywhere to record human movement -- from people cooking at home to workers in a textile workshop in India.

The stakes are higher than for a chatbot like ChatGPT. A robot acts in the physical world, so its mistakes can hurt someone.

"If you want to move into a more social domain, it really has to be safe for the users around the robot," said Valentino Fagard of Japan's XELA Robotics, which works on giving robots a sense of touch.

Engineers can set limits -- telling the machines not to grip too hard, or not to get too close to a person. But there is a catch. Like chatbots, these AI systems don't always behave the same way twice, which makes them hard to predict.

"The issue with, call it the world model, or the end-to-end VLA, is they're non-deterministic, they're a black box," said John Black of Brain Corp, whose robots stick to a very specific task, like cleaning floors or checking store shelves.

"They're nowhere close to reaching the safety levels required," he said, because even the people who build these systems can not fully see why they do what they do.

B.Martinez--TFWP