The Japan Times - Robots pour cocktails and run marathons, but still can't multitask

EUR -
AED 4.108631
AFN 72.718912
ALL 91.057672
AMD 404.138689
ANG 2.002333
AOA 1027.018171
ARS 1729.020675
AUD 1.621656
AWG 2.01376
AZN 1.909959
BAM 1.9623
BBD 2.256686
BDT 139.622493
BGN 1.955396
BHD 0.423298
BIF 3352.386487
BMD 1.118756
BND 1.435763
BOB 13.446541
BRL 6.151029
BSD 1.120471
BTN 105.220538
BWP 15.434677
BYN 3.355395
BYR 21927.614131
BZD 2.253477
CAD 1.576965
CDF 2595.514018
CHF 0.915886
CLF 0.027676
CLP 1089.229942
CNY 7.469377
CNH 7.462745
COP 3634.311854
CRC 508.137914
CUC 1.118756
CUP 26.891216
CVE 110.631461
CZK 24.354245
DJF 199.524609
DKK 7.475521
DOP 68.082658
DZD 152.34438
EGP 60.323863
ERN 16.781337
ETB 183.895683
FJD 2.534654
FKP 0.837714
GBP 0.834105
GEL 2.903189
GGP 0.837714
GHS 13.098388
GIP 0.837714
GMD 83.349337
GNF 9924.082884
GTQ 8.566376
GYD 235.008454
HKD 8.772763
HNL 30.114216
HRK 7.572869
HTG 146.824481
HUF 362.904219
IDR 20227.10528
ILS 3.543715
IMP 0.837714
INR 104.958595
IQD 1699.429275
IRR 2115962.181879
ISK 136.801282
JEP 0.837714
JMD 177.827184
JOD 0.793248
JPY 176.701327
KES 145.360104
KGS 97.835187
KHR 4564.917673
KMF 494.489717
KPW 1006.880197
KRW 1505.8227
KWD 0.347799
KYD 0.933863
KZT 502.232426
LAK 25207.443957
LBP 100335.927717
LKR 372.606055
LRD 190.571258
LSL 18.529735
LTL 3.303395
LVL 0.676724
LYD 7.17029
MAD 10.957897
MDL 20.027674
MGA 5091.407518
MKD 61.518753
MMK 2348.779066
MNT 4028.825441
MOP 9.049175
MRU 45.236008
MUR 52.670582
MVR 17.220986
MWK 1942.897957
MXN 20.773283
MYR 4.540802
MZN 71.483847
NAD 18.53015
NGN 1509.816716
NIO 41.23669
NOK 10.521328
NPR 168.271169
NZD 1.99359
OMR 0.430195
PAB 1.121114
PEN 3.861692
PGK 5.106565
PHP 70.755733
PKR 309.88721
PLN 4.384796
PYG 7003.819206
QAR 4.097774
RON 5.34374
RSD 117.634953
RUB 92.081868
RWF 1653.81688
SAR 4.207099
SBD 9.004399
SCR 15.485136
SDG 672.932625
SEK 10.994707
SGD 1.431901
SHP 0.837862
SLE 25.675065
SLL 23459.75515
SOS 640.326286
SRD 42.04676
STD 23155.986777
STN 24.570077
SVC 9.80849
SYP 14546.062858
SZL 18.523417
THB 37.472739
TJS 10.341155
TMT 3.915645
TND 3.354411
TOP 2.693695
TRY 56.138502
TTD 7.598536
TWD 36.737143
TZS 2959.106924
UAH 50.759638
UGX 4585.188208
USD 1.118756
UYU 45.099389
UZS 13376.308356
VES 1002.759193
VND 28545.614202
VUV 133.425135
WST 3.118894
XAF 655.957
XAG 0.02122
XAU 0.000272275241
XCD 3.023494
XCG 2.020292
XDR 0.791018
XOF 655.957
XPF 119.331742
YER 264.725556
ZAR 18.395545
ZMK 10070.139615
ZMW 22.767427
ZWL 360.238919
SSP 6427.512117
MXV 2.335285
  • RYCEF

    0.1000

    19.81

    +0.5%

  • VOD

    -0.2500

    16.33

    -1.53%

  • CMSC

    -0.2800

    20.12

    -1.39%

  • RBGPF

    -2.0000

    65

    -3.08%

  • RIO

    -0.2500

    94.16

    -0.27%

  • BTI

    -1.2000

    54.85

    -2.19%

  • NGG

    -0.3000

    74.94

    -0.4%

  • GSK

    -0.3500

    49.35

    -0.71%

  • BCE

    -0.4200

    20.14

    -2.09%

  • CMSD

    -0.3400

    19.93

    -1.71%

  • BP

    -0.9100

    43.52

    -2.09%

  • RELX

    0.1700

    33.24

    +0.51%

  • BCC

    -0.6200

    75.97

    -0.82%

  • AZN

    -1.9400

    164.21

    -1.18%

  • JRI

    0.0000

    10.77

    0%

Robots pour cocktails and run marathons, but still can't multitask
Robots pour cocktails and run marathons, but still can't multitask / Photo: JULIEN DE ROSA - 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.

Y.Hara--JT