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  • OpenAI claims its chip beats Nvidia 🌶️, d-Matrix introduces Raptor 🦖, Skild teaches tasks in 10 minutes 🎥

    From TLDR Hardware@VERT to tldrnewsletter@synchro.net on Wed Aug 26 13:15:37 2026
    --MP3oy_LH
    Content-Type: text/plain; charset=utf-8
    Content-Transfer-Encoding: quoted-printable

    OpenAI announced that its custom-designed AI inference processor,
    dubbed =
    Jalape=C3=B1o and developed in partnership with Broadcom,
    outperformed= =C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80= =8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0= =E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2= =A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C= =C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80= =8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2= =A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C= =C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80= =8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0= =E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2= =A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C=C2=A0=E2=80=8C= =C2=A0


    Sign Up [1] |Advertise [2]|View Online [3]=20

    =09=09TLDR=
    =20

    TLDR HARDWARE 2026-08-26

    =F0=9F=93=B1=20

    HEADLINES AND LAUNC=
    HES

    OPENAI CLAIMS CUSTOM JALAPE=C3=91O CHIP BYPASSES NVIDIA GB300 IN=

    EFFICIENCY BENCHMARKS (3 MINUTE READ) [4]=20

    OpenAI announced that i=
    ts custom-designed AI inference processor,
    dubbed Jalape=C3=B1o and devel=
    oped in partnership with Broadcom,
    outperformed Nvidia's flagship GB200 a=
    nd GB300 systems in internal
    benchmark evaluations. The custom silicon de=
    monstrated a 1.5x to 1.9x
    improvement in workload throughput per watt alo=
    ngside a 1.7x to 3.6x
    reduction in response latency across frontier reaso=
    ning and
    open-weights workloads like GPT-OSS, DeepSeek R1, and Kimi K2.5 =


    D-MATRIX STACKS LOGIC ON 3D DRAM TO TARGET 100 TB/S INFERENCE
    BAND=
    WIDTH (7 MINUTE READ) [5]=20

    d-Matrix's Raptor accelerator stacks an N4=
    logic die directly on 3D
    DRAM and uses stream blocking, pinless data-bus=
    inversion,
    thermal-aware refresh, and bank chaining to hold bandwidth ne=
    ar 100
    TB/s. The company claims a 72-card rack can serve a
    3-trillion-p=
    arameter-class model at 1M context at roughly 1,000 tokens
    per second per=
    user, but the live Hot Chips report explicitly says
    working-system evide=
    nce and drawbacks remain to be shown.=20

    =F0=9F=94=A8=20

    ENGINEERING =
    AND APPLICATIONS

    SAMSUNG ZHBM: DIRECT 3D DRAM STACKING REPLACES SILIC=
    ON INTERPOSERS (3
    MINUTE READ) [6]=20

    Samsung detailed its vision for=
    evolving HBM base dies from passive
    interposers into active logic, culmi=
    nating in "zHBM." By using hybrid
    copper bonding to mount DRAM stacks dir=
    ectly onto the processor die,
    the architecture removes power-hungry SERDE=
    S layers, cutting package
    power by ~100W on a 1,200W accelerator while bo=
    osting memory
    bandwidth.=20

    NVIDIA INTRODUCES JETSON ORIN NANO 2 FOR =
    ENTRY-LEVEL EDGE AI (4
    MINUTE READ) [7]=20

    NVIDIA's Jetson Orin Nano =
    2 is a lower-cost computer for robotics and
    edge inference. The module pa=
    ckages GPU compute, memory, and the
    Jetson software stack so builders can=
    prototype perception and control
    without a server connection. Performanc=
    e and efficiency figures are
    first-party, and suitability depends on the =
    actual model and power
    envelope.=20

    =F0=9F=A7=A0=20

    RESEARCH AND PR=
    OTOTYPES

    SKILD AI'S S1 LEARNS 10-MINUTE ROBOT TASKS FROM A SINGLE VID=
    EO, NO
    FINE-TUNING (3 MINUTE READ) [8]=20

    Skild AI's S1 is a foundati=
    on model that performs in-context learning
    for robotics, meaning it can b=
    e shown a single video of a long-horizon
    task, over 10 minutes long and n=
    ever seen during pre-training, and
    then execute it without any fine-tunin=
    g. It's a meaningful step beyond
    typical robot foundation models, which u=
    sually need dedicated training
    data for each new task rather than picking=
    one up on the fly from a
    single demonstration. This fits a broader patte=
    rn this year of
    general-purpose robot models learning tasks purely from e=
    xamples,
    following similar early demos from Rhoda and Generalist, with Sk=
    ild's
    version notably extending the horizon out to a full 10 minutes.=20
    =

    FIGURE AI LAUNCHES INDEX, TRAINING ITS ROBOTS ON 16 MILLION
    CROWDSOUR=
    CED UPLOADS (4 MINUTE READ) [9]=20

    Figure AI has come out of stealth wi=
    th Index, a crowdsourced data
    platform that's already collected 16 millio=
    n video uploads from over
    264,000 app downloads across 108 countries, pay=
    ing contributors $15
    million so far to film themselves doing everyday tas=
    ks like opening
    drawers or folding laundry. The bet addresses robotics' c=
    ore data
    bottleneck: language models could train on internet text, but em=
    bodied
    AI needs real-world physical demonstrations that simply don't exis=
    t
    online at scale. Figure is committing over $1 billion to data and
    com=
    pute over the next 12 months to close that gap.=20

    =F0=9F=8E=81=20

    MI=
    SCELLANEOUS

    IBM UNVEILS NEXT-GENERATION DUAL-ARCHITECTURE PROCESSOR F=
    OR IBM Z AND
    LINUXONE (3 MINUTE READ) [10]=20

    IBM announced its first=
    dual-ISA mainframe processor at Hot Chips
    2026, engineered to natively e=
    xecute both IBM z/Architecture and
    Armv9.3-A instructions on the same phy=
    sical cores. Fabricated on a 2nm
    process node, the chip features 11 high-=
    performance cores clocked
    above 5.7 GHz, integrated AI inference accelera=
    tion, a dedicated
    on-chip Data Processing Unit (DPU) for I/O offload, and=
    large
    enterprise cache tiers. Rather than using separate physical cores =
    in a
    heterogeneous layout, each core dynamically switches between
    z/Arc=
    hitecture and AArch64 execution within nanoseconds, enabling
    organization=
    s to run unmodified Arm-native Linux software and modern
    AI frameworks co=
    ncurrently alongside mission-critical z/OS transaction
    systems.=20

    FI=
    RST LOOK INSIDE APPLE'S AI SERVERS REVEALS A DENSELY PACKED
    M-SERIES DESI=
    GN (3 MINUTE READ) [11]=20

    Leaked photos of a custom 2U rack server, re=
    portedly from Apple's
    Houston manufacturing facility, show its Private Cl=
    oud Compute
    hardware for the first time. Each unit packs four columns of =
    eight
    boards apiece (32 chips total), with a single Apple Silicon package=
    at
    the center of each board flanked by removable brackets, all cooled by=

    one fan per column pulling air front-to-back through a
    plastic-enclose=
    d passage. Forum analysis of the board sizes suggests
    these are more like=
    ly base M5-class packages rather than the M5 Ultra
    chips previously rumor=
    ed, since an Ultra package (two dies plus eight
    memory chips) would be ro=
    ughly four times larger than what's visible
    in the photos, and the heatsi=
    nks look undersized for a 150-watt chip=20

    =E2=9A=A1=20

    QUICK LINKS=


    INTEL UNVEILS ARCHITECTURE ROADMAP FOR AGENTIC AI (3 MINUTE READ)
    =
    [12]=20

    Intel has previewed architectural enhancements in its upcoming=

    Diamond Rapids, Crescent Island, and Wildcat Lake processors targeted
    =
    at agentic AI workloads.=20

    OURA REPORTEDLY EYEING A SEPTEMBER IPO THAT=
    COULD VALUE IT ABOVE $16B
    (2 MINUTE READ) [13]=20

    Smart ring maker O=
    ura is reportedly planning to raise up to $3
    billion in a US IPO as soon =
    as next month, valuing the company at over
    $16 billion.=20

    AMD UNVEIL=
    S INSTINCT MI455X & HELIOS 72-GPU RACK ARCHITECTURE (4
    MINUTE READ) [14] =


    AMD has revealed full details for its next-generation Instinct MI455=
    X
    accelerator and Helios rack platform.=20

    INTEL EMIB-T SECURES SK HY=
    NIX HBM QUALIFICATION TO EASE PACKAGING
    CRUNCH (3 MINUTE READ) [15]=20
    =

    SK hynix and Intel Foundry are collaborating to package
    next-generati=
    on HBM memory using Intel's EMIB-T 2.5D bridge
    technology.=20

    SPACEX'=
    S MUSK SEES ORBITAL DATA CENTER LAUNCH NEAR END OF 2027 (3
    MINUTE READ) [=
    16]=20

    Elon Musk stated that SpaceX aims to launch its initial fleet of=

    orbital AI data centers by late 2027, powered by Nvidia hardware
    archi=
    tecture.=20

    Want to advertise in TLDR? =F0=9F=93=B0

    If your compan=
    y is interested in reaching an audience of hardware
    professionals and dec=
    ision makers, you may want to ADVERTISE WITH US
    [17].=20

    Want to work =
    at TLDR? =F0=9F=92=BC

    APPLY HERE [18], CREATE YOUR OWN ROLE [19] or s=
    end a friend's resume
    to jobs@tldr.tech and get $1k if we hire them! TLDR=
    is one of INC.'S
    BEST BOOTSTRAPPED BUSINESSES [20] of 2025.=20

    If yo=
    u have any comments or feedback, just respond to this email!=20

    Thanks f=
    or reading,=20
    Kshitij Sudan [21] & Adi Nikumbh [22]=20

    Manage your sub=
    scriptions [23] to our other newsletters on tech,
    startups, and programmi=
    ng. Or if TLDR Hardware isn't for you, please
    unsubscribe [24].=20

    =


    Links:
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    [4] https://news= letter.semianalysis.com/p/openai-jalapeno-better-than-nvidia?utm_source=3Dt= ldrhardware
    [5] https://www.servethehome.com/d-matrix-raptor-3d-dram-acce= lerator-for-generative-inference-at-hot-chips-2026/?utm_source=3Dtldrhardwa=
    re
    [6] https://www.servethehome.com/samsung-evolving-hbm-base-die-at-hot-= chips-2026/?utm_source=3Dtldrhardware
    [7] https://nvidianews.nvidia.com/n= ews/nvidia-announces-jetson-orin-nano-2-robotics-computer-to-redefine-entry= -level-edge-ai?utm_source=3Dtldrhardware
    [8] https://digg.com/tech/rbnvsc=
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    [10] https://newsroom.ibm.com/2026-08-24-ibm-unveils= -next-generation-dual-architecture-processor-for-ibm-z-and-linuxone?utm_sou= rce=3Dtldrhardware
    [11] https://appleinsider.com/articles/26/08/24/this-i= s-the-first-look-at-the-inside-of-apples-ai-servers?utm_source=3Dtldrhardwa=
    re
    [12] https://newsroom.intel.com/client-computing/intel-outlines-archit= ectures-for-agentic-ai-at-hot-chips-2026?utm_source=3Dtldrhardware
    [13] h= ttps://techcrunch.com/2026/08/24/oura-is-reportedly-eyeing-a-september-ipo-= that-could-value-it-at-more-than-16b/?utm_source=3Dtldrhardware
    [14] http= s://www.servethehome.com/amd-helios-mi400-system-architecture-at-hot-chips-= 2026/?utm_source=3Dtldrhardware
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    =09=09=09<![endif]--></head><body class=3D"">



    <div style=3D"display: none; max-height: 0px; overflow: hidden;">OpenAI ann= ounced that its custom-designed AI inference processor, dubbed Jalape=C3=B1=
    o and developed in partnership with Broadcom, outperformed&nbsp;=E2=80=8C&n= bsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&n= bsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&n= bsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&n= bsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&n= bsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&n= bsp;&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2= =80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2= =80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2= =80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2= =80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2=80=8C&nbsp;=E2= =80=8C&nbsp;=E2=80=8C&nbsp;</div>

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    <div style=3D"text-align: center;">

    <h1><strong>TLDR Hardware <span id=3D"date">2026-08-26</span></strong></h1> </div>
    </td></tr></tbody></table>

    <table style=3D"table-layout: fixed; width:100%;" width=3D"100%"><tbody></t= body></table>
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    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td style=3D"padding: 0px;">

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;"><span style=3D"font-size: 36px;">=F0=9F= =93=B1</span></div></div>
    </td></tr></tbody></table>

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;">

    <h1><strong>Headlines and Launches</strong></h1>
    </div>
    </div>
    </td></tr></tbody></table>

    <table style=3D"table-layout: fixed; width: 100%;" width=3D"100%"><tbody><t= r><td style=3D"padding:0;border-collapse:collapse;border-spacing:0;margin:0=
    ;" valign=3D"top">

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fnewsletter.semianalysis.com%2Fp%2Fopenai-jalapeno-bette= r-than-nvidia%3Futm_source=3Dtldrhardware/1/010001a03e363ed4-8864a095-ae26-= 4322-b621-eb85744a1499-000000/wGJ75E2dq6kK92DasHvhcT1QxzDrkuQsXEIcwQOohYA= =3D452">
    <span>
    <strong>OpenAI Claims Custom Jalape= =C3=B1o Chip Bypasses Nvidia GB300 in Efficiency Benchmarks (3 minute read)= </strong>
    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    OpenAI announced that its custom-design=
    ed AI inference processor, dubbed Jalape=C3=B1o and developed in partnershi=
    p with Broadcom, outperformed Nvidia's flagship GB200 and GB300 systems in = internal benchmark evaluations. The custom silicon demonstrated a 1.5x to 1= .9x improvement in workload throughput per watt alongside a 1.7x to 3.6x re= duction in response latency across frontier reasoning and open-weights work= loads like GPT-OSS, DeepSeek R1, and Kimi K2.5
    </span>
    </span>
    </div>
    </td></tr></tbody></table>

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fwww.servethehome.com%2Fd-matrix-raptor-3d-dram-accelera= tor-for-generative-inference-at-hot-chips-2026%2F%3Futm_source=3Dtldrhardwa= re/1/010001a03e363ed4-8864a095-ae26-4322-b621-eb85744a1499-000000/0d_VDf-og= -I7KOwG1DrgFQP0wn0pYXRDqvwvyTnemHo=3D452">
    <span>
    <strong>d-Matrix stacks logic on 3D=
    DRAM to target 100 TB/s inference bandwidth (7 minute read)</strong>
    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    d-Matrix's Raptor accelerator stacks an=
    N4 logic die directly on 3D DRAM and uses stream blocking, pinless data-bu=
    s inversion, thermal-aware refresh, and bank chaining to hold bandwidth nea=
    r 100 TB/s. The company claims a 72-card rack can serve a 3-trillion-parame= ter-class model at 1M context at roughly 1,000 tokens per second per user, = but the live Hot Chips report explicitly says working-system evidence and d= rawbacks remain to be shown.
    </span>
    </span>
    </div>
    </td></tr></tbody></table>

    </td></tr></tbody></table>

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;"><span style=3D"font-size: 36px;">=F0=9F= =94=A8</span></div>
    </div>
    </td></tr></tbody></table>

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;">

    <h1><strong>Engineering and Applications</strong></h1>
    </div>
    </div>
    </td></tr></tbody></table>


    <table style=3D"table-layout: fixed; width: 100%;" width=3D"100%"><tbody><t= r><td style=3D"padding:0;border-collapse:collapse;border-spacing:0;margin:0=
    ;" valign=3D"top">

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fwww.servethehome.com%2Fsamsung-evolving-hbm-base-die-at= -hot-chips-2026%2F%3Futm_source=3Dtldrhardware/1/010001a03e363ed4-8864a095-= ae26-4322-b621-eb85744a1499-000000/5T-MbKe_8Q9huqN70fJEFUwoFrZVEsCY0zBoVkFg= blw=3D452">
    <span>
    <strong>Samsung zHBM: Direct 3D DRA=
    M Stacking Replaces Silicon Interposers (3 minute read)</strong>
    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    Samsung detailed its vision for evolvin=
    g HBM base dies from passive interposers into active logic, culminating in = "zHBM." By using hybrid copper bonding to mount DRAM stacks directly onto t=
    he processor die, the architecture removes power-hungry SERDES layers, cutt= ing package power by ~100W on a 1,200W accelerator while boosting memory ba= ndwidth.
    </span>
    </span>
    </div>
    </td></tr></tbody></table>

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fnvidianews.nvidia.com%2Fnews%2Fnvidia-announces-jetson-= orin-nano-2-robotics-computer-to-redefine-entry-level-edge-ai%3Futm_source= =3Dtldrhardware/1/010001a03e363ed4-8864a095-ae26-4322-b621-eb85744a1499-000= 000/GNMRdkREVi87hSlzxOq1LZpYI5wc-NR6NigM1H0SvZ0=3D452">
    <span>
    <strong>NVIDIA introduces Jetson Or=
    in Nano 2 for entry-level edge AI (4 minute read)</strong>
    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    NVIDIA's Jetson Orin Nano 2 is a lower-= cost computer for robotics and edge inference. The module packages GPU comp= ute, memory, and the Jetson software stack so builders can prototype percep= tion and control without a server connection. Performance and efficiency fi= gures are first-party, and suitability depends on the actual model and powe=
    r envelope.
    </span>
    </span>
    </div>
    </td></tr></tbody></table>

    </td></tr></tbody></table>

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;"><span style=3D"font-size: 36px;">=F0=9F= =A7=A0</span></div>
    </div>
    </td></tr></tbody></table>

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;">

    <h1><strong>Research and Prototypes</strong></h1>
    </div>
    </div>
    </td></tr></tbody></table>

    <table style=3D"table-layout: fixed; width: 100%;" width=3D"100%"><tbody><t= r><td style=3D"padding:0;border-collapse:collapse;border-spacing:0;margin:0=
    ;" valign=3D"top">

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fdigg.com%2Ftech%2Frbnvscse%3Futm_source=3Dtldrhardware/= 1/010001a03e363ed4-8864a095-ae26-4322-b621-eb85744a1499-000000/h_SEJyxGgGgz= RHAWBb6sxmwuW7X6OryV3dFA05UczE0=3D452">
    <span>
    <strong>Skild AI's S1 learns 10-min= ute robot tasks from a single video, no fine-tuning (3 minute read)</strong=

    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    Skild AI's S1 is a foundation model tha=
    t performs in-context learning for robotics, meaning it can be shown a sing=
    le video of a long-horizon task, over 10 minutes long and never seen during=
    pre-training, and then execute it without any fine-tuning. It's a meaningf=
    ul step beyond typical robot foundation models, which usually need dedicate=
    d training data for each new task rather than picking one up on the fly fro=
    m a single demonstration. This fits a broader pattern this year of general-= purpose robot models learning tasks purely from examples, following similar=
    early demos from Rhoda and Generalist, with Skild's version notably extend= ing the horizon out to a full 10 minutes.
    </span>
    </span>
    </div>
    </td></tr></tbody></table>

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fglitchwire.com%2Fnews%2Ffigure-ai-announces-index-a-cro= wdsourced-robot-training-dataset-that-could-resha%2F%3Futm_source=3Dtldrhar= dware/1/010001a03e363ed4-8864a095-ae26-4322-b621-eb85744a1499-000000/zPKuW6= S3msVRkTplZOUb8bkWV3_rwaw8QYmZlPa45aU=3D452">
    <span>
    <strong>Figure AI launches Index, t= raining its robots on 16 million crowdsourced uploads (4 minute read)</stro=

    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    Figure AI has come out of stealth with = Index, a crowdsourced data platform that's already collected 16 million vid=
    eo uploads from over 264,000 app downloads across 108 countries, paying con= tributors $15 million so far to film themselves doing everyday tasks like o= pening drawers or folding laundry. The bet addresses robotics' core data bo= ttleneck: language models could train on internet text, but embodied AI nee=
    ds real-world physical demonstrations that simply don't exist online at sca= le. Figure is committing over $1 billion to data and compute over the next =
    12 months to close that gap.
    </span>
    </span>
    </div>
    </td></tr></tbody></table>

    </td></tr></tbody></table>

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;"><span style=3D"font-size: 36px;">=F0=9F= =8E=81</span></div></div>
    </td></tr></tbody></table>

    <table align=3D"center" bgcolor=3D"" border=3D"0" cellpadding=3D"0" cellspa= cing=3D"0" width=3D"100%"><tbody><tr><td class=3D"container" style=3D"paddi= ng-top: 0px; padding-bottom: 0px;">
    <div class=3D"text-block">
    <div style=3D"text-align: center;"><strong><h1>Miscellaneous</h1></strong><= /div>
    </div>
    </td></tr></tbody></table>

    <table bgcolor=3D"" style=3D"table-layout: fixed; width: 100%;" width=3D"10= 0%"><tbody><tr><td style=3D"padding:0;border-collapse:collapse;border-spaci= ng:0;margin:0;" valign=3D"top">

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fnewsroom.ibm.com%2F2026-08-24-ibm-unveils-next-generati= on-dual-architecture-processor-for-ibm-z-and-linuxone%3Futm_source=3Dtldrha= rdware/1/010001a03e363ed4-8864a095-ae26-4322-b621-eb85744a1499-000000/PFE9Q= jXxbZYqxuTR_t3x0UrxMUivVlk30xsmQGvIB-4=3D452">
    <span>
    <strong>IBM Unveils Next-Generation=
    Dual-Architecture Processor for IBM Z and LinuxONE (3 minute read)</strong=

    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    IBM announced its first dual-ISA mainfr= ame processor at Hot Chips 2026, engineered to natively execute both IBM z/= Architecture and Armv9.3-A instructions on the same physical cores. Fabrica= ted on a 2nm process node, the chip features 11 high-performance cores cloc= ked above 5.7 GHz, integrated AI inference acceleration, a dedicated on-chi=
    p Data Processing Unit (DPU) for I/O offload, and large enterprise cache ti= ers. Rather than using separate physical cores in a heterogeneous layout, e= ach core dynamically switches between z/Architecture and AArch64 execution = within nanoseconds, enabling organizations to run unmodified Arm-native Lin=
    ux software and modern AI frameworks concurrently alongside mission-critica=
    l z/OS transaction systems.
    </span>
    </span>
    </div>
    </td></tr></tbody></table>

    <table align=3D"center" border=3D"0" cellpadding=3D"0" cellspacing=3D"0" wi= dth=3D"100%"><tbody><tr><td class=3D"container" style=3D"padding: 15px 15px=

    <div class=3D"text-block">
    <span>
    <a href=3D"https://tracking.tldrnewsletter.= com/CL0/https:%2F%2Fappleinsider.com%2Farticles%2F26%2F08%2F24%2Fthis-is-th= e-first-look-at-the-inside-of-apples-ai-servers%3Futm_source=3Dtldrhardware= /1/010001a03e363ed4-8864a095-ae26-4322-b621-eb85744a1499-000000/6_PnkHWINrp= okXmU7MJfmFFl6L01imvAX2ZMt1OXASk=3D452">
    <span>
    <strong>First look inside Apple's A=
    I servers reveals a densely packed M-series design (3 minute read)</strong>
    </span>



    <span style=3D"font-family: &quot;Helvetica Neue&quot;, Helvetica, Arial, V= erdana, sans-serif;">
    Leaked photos of a custom 2U rack serve=
    r, reportedly from Apple's Houston manufacturing facility, show its Private=
    Cloud Compute hardware for the first time. Each unit packs four columns of=
    eight boards apiece (32 chips total), with a single Apple Silicon package =
    at the center of each board flanked by removable brackets, all cooled by on=
    e fan per column pulling air front-to-back through a plastic-enclosed passa= ge. Forum analysis of the board sizes suggests these are more likely base M= 5-class packages rather than the M5 Ultra chips previously rumored, since a=
    n Ultra package (two dies plus eight memory chips) would be roughly four ti= mes larger than what's visible in the photos, and the heatsinks look unders= ized for a 150-watt chip
    </span>
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